Transcript Biopath (BMOND) – A NEW APPROACH TO FORMAL …

BioUML – integrated platform for building
virtual cell and virtual physiological human
Fedor
1,2
Kolpakov ,
1,2
Tolstykh ,
1,2
Kutumova ,
Nikita
Elena
Ilya
1,2
1,3
1,3
Aleksey Shadrin , Tagir Valeev , Anna Ryabova
0100100010011101
ISB
1,2
Kiselev ,
1Institute
of Systems Biology, Novosibirsk, Russia;
2Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia
3A.P. Ershov Institute of Invormatics Systems SB RAS, Novosibirsk, Russia;
*Contacts: [email protected]
Main features
Motivation
Reconstruction of complex biological systems and consequent building of
virtual cell and virtual physiological human requires integrated
platform that provides:
1. integration with a wide range of biological databases;
2. integration with omics data;
3. powerful search capabilities;
4. decomposition of complex biological systems into blocks and modules;
5. visual modeling, multi-scale modeling, agent based modeling;
6. multi-experiment parameters fitting
7. powerful data analyses capabilities
8. support of reproducible research
9. client-server architecture for team work.
BioUML platform
BioUML is an open source integrated platform for systems biology that
spans the comprehensive range of capabilities including access to
databases with experimental data, tools for formalized description,
visual modeling and analyses of complex biological systems.
Due to usage of scripting langauges (R, JavaScript) and workflow support
it provides powerful possibilities for analyses of high-throughput data.
Plug-in based architecture (Eclipse run time from IBM is used) allows to
add new functionality using plug-ins.
BioUML platform consists from 3 parts:
1. BioUML server - provides access to data and analyses methods installed
on the server side for BioUML clients (workbench and web edition) via
the Internet.
2. BioUML workbench - Java application that can work standalone or as
"thick" client for BioUML server.
3. BioUML web edition - "thin" client for BioUML server (you just need
to start web browser) that provides most of functionality of BioUML
workbench. It uses AJAX and HTML5 <canvas> technology for visual
modeling and interactive data editing.
 supports main standards in systems biology
 visual modeling
– SBML - Systems Biology Markup Language.
BioUML supports SBML Level 1 version 1-2; Level 2 versions 1-4;
Level 3 version 1. BioUML is the only simulator that have passed all
tests from SBML test suite version 2.0
– SBGN - Systems Biology Graphic Notation.
BioUML supports Process Diagrams as they are defined by SBGN
version 1.0.
– BioPAX - Biological Pathway Exchange.
BioUML can import data in BioPAX 2.0 format. Imported data can be
stored as native BioPAX file, SQL or text database.
– PSI-MI - The Proteomics Standards Initiative Molecular Interaction
XML format.
– OBO - Ontology Flat File Format.
BioUML can import ontology in OBO 1.2 format. Imported data can be
presented as semantic networks.
– CellML - Cell Markup Language .
BioUML can read and simulated biochemical models presented in
CellML 1.0 format.
– powerful diagram editor
– virtual experiment - variations of diagram to simulate different
experimental conditions, knock-outs, etc.
– automated generation of optimized Java code for model simulation
from corresponding pathway diagram
– different solvers for differential equations:
 JVODE - ported to Java version of CVODE
 RADAU IIA - (implicit Runge-Kutta method for stiff delay
differential equations)
 Imex - (implicit Runge-Kutta method for stiff differential
equations)
 Dormand-Prince - (explicit Runge-Kutta method)
 Euler (for debugging complex models)
– supports different model types:
 ODE - odinary differential equations
 DAE - differential algebraic equations
 ODE/DAE with delay
 1D PDE (for blood flow simulation)
 hybrid models support (with events, states and transitions)
 hierarchical models
– plots (using JFreeChart)
 time series
 phase portrait
 supports main biological databases
– catalolgs: Ensembl, UniProt, ChEBI, GO
– pathways: KEGG, Reactome, EHMN, BioModels, TRANSPATH,
EndoNet, BMOND
 powerful search possibilities
 parameters fitting
– full text search (Apache Lucene is used)
– graph search - finds related pathway components and presents results
as an editable graph
– experimental data - time courses or steady states
– experimental data - exact or relative values of substance or
concentrations
– multiexperiment fitting
– global and local parameters for multiexperiment fitting
– constraint support
– different optimization methods
 Adaptive Simulating Annealing
 Cellular genetic algorithm
 Evolution strategy (SRES)
 GLBSOLVE
 Particle swarm optimization
 Quadratic Hill-climbing
– optimization and parallelization of computations
– JavaScript API for parameters fitting
 reports, templates
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different templates for representing data element info
model reports
Overview
Reactions
 Parameters
 Variables
 ODE(model as differential equation system)
 graph layout engine
– includes different layout algorithms:
 force directed layout
 hierarchical layout
 cross grid layout
 fast grid layout
– support incremental graph layout
– support compartments
– layout preview
– possibility to reuse layout for similar diagrams
 data analyses
– supports a set of analysis method
 biosequence analysis
 gene expression regulation modeling
 model optimization
 statistics
– executing analysis from JavaScript
 genome browser
Mitochondrion module in SBGN notation
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 microarray analyses
uses AJAX and HTML5 <canvas> technologies (BioUML web edition)
interactive - dragging, semantic zoom
DAS support (Distributed Annotation System)
tracks support
 Ensembl tracks
 DAS tracks
 user-loaded BED/GFF/Wiggle files
script console
JavaSsript editor
JavaScript debugger (BioUML workbench only)
JavaScript preprocessor (allows to embed easily R expressions)
 R support
Genome browser
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normalization
annotation
up and down identification
correlation analysis
hypergeometric meta-analysis
cluster analysis
 workflow, reproducible research
 JavaScript support
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connect to R on local or remote machine
convert BioUML data to R and save R results as BioUML data
R graphics support
R preprocessor for JavaScript
 SQL support
– SQL console
– direct SQL access to analysis results tables
– journal actions
 Analysis
 JavaScript
 SQL requests
– allows to present set of actions in research diagram
– allows to build and execute workflow document
 plug-in based architecture
– based on Eclipse runtime
– allows to integrate other tools: SBW, R, Matlab, CDK, Lucene, ...
Acknowledgements
This work was supported by FP6 grant 037590 “Net2Drug”, FP7 grant
090107 "LipidomicNet" and interdisciplinary project 46 of SB RAS.
Availability
http://www.biouml.org
Workflow