Slide 1

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 2

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 3

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 4

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 5

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 6

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 7

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 8

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 9

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 10

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 11

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 12

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 13

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 14

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 15

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 16

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 17

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 18

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 19

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 20

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 21

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 22

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 23

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 24

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 25

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 26

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 27

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

Franck Delaplace - Berder 2012

4

What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

Franck Delaplace - Berder 2012

5

computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

6

Franck Delaplace - Berder 2012

7

Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

Franck Delaplace - Berder 2012

8

Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

Franck Delaplace - Berder 2012

9

Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

Franck Delaplace - Berder 2012

10

Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

11

Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

12

Franck Delaplace - Berder 2012

13

Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

Franck Delaplace - Berder 2012

14

Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

15

Franck Delaplace - Berder 2012

16

Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

Franck Delaplace - Berder 2012

17

CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

Franck Delaplace - Berder 2012

18

Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

Franck Delaplace - Berder 2012

19

Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

Franck Delaplace - Berder 2012

20

Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

Franck Delaplace - Berder 2012

21

Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

Franck Delaplace - Berder 2012

22

Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

Franck Delaplace - Berder 2012

23

Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

Franck Delaplace - Berder 2012

24

Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

25

Franck Delaplace - Berder 2012

26

Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

Franck Delaplace - Berder 2012

27

Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

28


Slide 28

Franck Delaplace - Berder 2012

BIOLOGY & COMPUTING
Franck Delaplace
IBISC – Evry University - Genopole
BERDER 2012

1

Franck Delaplace - Berder 2012

Synthetic Biology in a Nutshell
• Multi disciplinary approach
• design of synthetic bio-systems
• Engineering principles
Design  Assembly of BIOBRICKS

Kwok -Nat. 463 Jan. 2010

2

Franck Delaplace - Berder 2012

3

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What I cannot compute,
I cannot understand …
HOPE SO !
Computing
=
Understanding

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computation Biology
Life as model of computation

Computing with Life

Synthetic Biology
Programming Life

computation model as a model of Life

Franck Delaplace - Berder 2012

BIO-INSPIRED
ALGORITHMS & MODELS
Life as model of computation

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Bio-Inspired algorithms
• Computation Framework
• For a large class of problems
• Meta heuristic

Genetic Algorithm
J. Holland - Goldberg

• For complex problems
• Intractable  NP complete
• IA problems (Design)

Swarm algorithm

• Common Features
• Population, Society
• Local operations
• Global evaluation
• Randomness

Neural networks

M. Dorigo, V.Maniezzo,
et A. Colorni

Hopfield – Rosenblatt

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Genetic algorithm - Bridge Design
Darwinian Paradigm

Mutation

Fitness
ranking

Cross
over

Selection

Funes, Pablo, Lapat, Louis and
Pollack, Jordan B. EvoCAD:
Evolution-Assisted Design.
Artificial Intelligence in Design'00

 Agent = Genome coding for a bridge

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Bio-Inspired models
Turing machine = “common ancestor”

Membrane computing
G. Paun
L – Systems

• New computing model
• Alternative computation
medium
• New computing rules
• Computational power
• Turing universality :
Simulation of a computer
(universal Turing machine)
• Massive parallelism :
combinatorial resolution of NP
complete problems

A. Lindenmayer,
P. Prusinkiewicz
Cellular Automata
J. Von Neuman - S. Wolfram

DNA computing
Adleman – G. Paun, G.
Rozenberg

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Example Membrane computing
• P-System
• Non determinism
• Evolution strategy 

maximal parallel
• Application
• Sorting

Skin
Membrane
Rules

𝑥 →𝑦
𝑑 →𝛿

• NP complete problem

(TSP)
• Verification of
cryptography protocol

𝑒 → 𝑑𝑜𝑢𝑡

Objects

𝑎

𝑏
𝑎𝑏 → 𝑐

Franck Delaplace - Berder 2012

SYSTEMS BIOLOGY
computation as a model of biological processes

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Franck Delaplace - Berder 2012

computation-inspired framework
« De toute évidence, la cohérence fonctionnelle d'une
machine chimique aussi complexe, et en outre
autonome, exige l'intervention d'un système
cybernétique gouvernant et contrôlant l'activité
chimique en de nombreux points. » (p. 59)

• “Cybernétique moléculaire”
• Circuit / Network explanatory

framework of biological
process
• Logical Network (R.Thomas)

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Formal models
• Discrete dynamics
• State based
• Formal property analysis
• Safety
• Reachability / invariance
• Explanatory framework
• Formalization of Biological
process
• Phenotype = molecular
signature  equilibria

State

Transition

State

Automata
Petri net
Process algebra
Game theory
Membrane comp.

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Example - Automata based model
101

a
b

111

001

100

c

a = NOT c
b=a
c = NOT b

Specification

011

110

000

010
a

Dynamics

b

c

Franck Delaplace - Berder 2012

SYNTHETIC BIOLOGY
Programming/designing living organism

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Design-manufacturing  compilation
main(){
Printf
(“Hello World”);
}

Program

Compilation

Execution
Computer

Synthetic Biology

Synthesis

SB function

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CAD Environment (ideal) Overview
High level
Program
Interface

Translator/
Compiler

Low level
Program

Sequence
Validation/
Optimization

Synthesis

Dedicated
Specification

Parts

Database

Safety
Security
Checking

Dynamics
Analysis

Simulator

Integrated view from the current states of art

Genetic
Engineering

Trace
Report

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Compilation principles in a nutshell

ADD R5,R6,R7
LDC 3, R5

MEMORY

LDC 4,R2
LDC 3, R5

DIV R4,R3,R6

LD &K, R1
MUL R2,R1,R4

MUL R2,R1,R4

LD R3, &J

ST V,Ry

REGISTER

LD R3, &J
ADD R5,R6,R7

LDC 4,R2

LD V,Rx

UAL

LD &K, R1

OP R1,R2,R3

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Languages for SB  Structural description
(GEC [Pedersen,Plotkin])
r0040:prom;b0034:rbs;c0040:prc;X:ter
R0040

(Genocad [Peccoud] )

b0034

c0040

X

• Program = sequence description
• Usual in language & CAD Env.
• Genocad, GEC, Kera
• Clotho, Eugène, Tinker Cell, …

GENE
PROM

• Grammar rules = guide of design

CODING SEQ

• Structural description
• Low level (DNA sequence)

START

RBS

PROT

STOP

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Structural vs. behavioral description
• Structure
• component assembly
description
• Low level of description
• Back end
• Behavior/function
• Process design
• Functional  safety
• High level of description
• Specification/document

Hardware Description Language
Verilog - VHDL

Behavioral
program

Generate Oil
Y when X

X

Structural
program

Y

r0040:prom;b0034:rbs;..

ATG|AAA|TTG|…

Synthesis
Toy example

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Compilation 
Part assembly = behavior assembly
• Component description = behavior description

• Bio system design = behavior description
• The program describes the expected “function”
• The issue is to define a compilation method assembling parts such

that the behavior of the assembly is “similar” to the behavior of the
designed function.
• Problem - Reliability  guaranty on the assembly
• i.e. formal guaranty that each step is correct w.r.t. to the behavioral
“similarity”.
Correct translation (compilation) ?

X

Y
Program

Prom X

b0034

Y

Assembly

b0015

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Behavior compilation for SB - 2 possible ways
Computational description
• Behavior = Abstract machine instruction
• Synthesis = Semantic rules

Logical Specification
• Behavior = Specification
• Synthesis = Proof rules

Dessine moi
un canard !

Axioms
Behavior of components

State = Situation
Event-driven
transition
State = Situation

Proof
Theorem
Behavior of the function

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Model & theory in logic
Is a formula true ?
Completeness

Model

Theory

Correction
Interpretation

Deduction system

𝐼 𝑏 = 1, 𝐼 𝑐 = 1

𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

𝐼 𝑏 𝑐 = max 𝐼 𝑏 , 𝐼 𝑐
𝐼(b ∧ c)= min(𝐼 𝑏 , 𝐼 𝑐 )
OR

0

1

0

0

1

1

1

1

𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑
𝑏 ∧ 𝑐 𝑖𝑠 𝑝𝑟𝑜𝑣𝑒𝑑

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Correction of the assembly
Correction of assembly = observational behavior inclusion

Compilation = Proof  find a behavior assembly s.t.
the behavior of the designed function is included
Part A

Part B

AATTGGAAGCC

AATGCGTTTATAGCCCCATGG..

Franck Delaplace - Berder 2012

Remarks
• Functional/behavioral programming
• 1 function  n structures – e.g. inhibition • Document function  Safety analysis capability
• Proof framework
• Safe design  formal method + safety analysis
• Functional/qualitative description  Specification, resolution principles
• Quantitative description  Strategy of the resolution, tuning
• Hierarchy of the components ≠ Organization for organisms
• Functionality
• Inter-operability
• GUBS project - Adrien Basso Blandin – Franck Delaplace
• Behavioral language
• Compiler

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Synbiotic : Tower of languages
Global
specification

Local
Specification

• Population level
• Global programming

IBISC
Franck Delaplace
Jean-Louis Giavitto
Hanna Klaudel
Franck Pommereau
Sylvain Sené
Adrien Basso
LACL

• Agent centric
• Elementary behavior

Olivier Michel
Gaetan Hains
Antoine Spicher
Serghei Verlan

GUBS
CREA - ISC

Implementation

Nature 434:
Basu S & al.

• Interface
in-silico / In vivo
• Regulatory network

René Doursat
Paul Bourgine
Taras Kowaliw

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Conclusion
Life as model of computation

• Function
• Process

Computing with Life
Synthetic Biology
Programming Life

computation model as a model of Life

Behavioral Language
for synthetic biology

Franck Delaplace - Berder 2012

THANK YOU !

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