Transcript A.A. 2008-2009 CORSO DI BIOINFORMATICA per il CLT in

A.A. 2013-2014
CORSO INTEGRATO DI
INFORMATICA E
BIOINFORMATICA
per il CLT in BIOLOGIA MOLECOLARE
Scuola di Scienze, Università di Padova
Docenti: Dr. Mauro Conti (Informatica) e
Dr. Stefania Bortoluzzi (Bioinformatica)
SVOLGIMENTO DEL CORSO INTEGRATO
E MODALITÀ D’ESAME
• II semestre del I anno
• Impegno didattico di 5 crediti:
• 24 ore di lezione frontale
• 32 ore di esercitazioni al computer
Così suddivise:
Insegnamento
Lezione
Esercitazione
INFORMATICA
16
16
BIOINFORMATICA
8
16
• Valutazione finale (Idoneità): in base all’esito delle
esercitazioni e di una verifica scritta individuale.
WEB SITE DEDICATO AL CORSO
http://compgen.bio.unipd.it/~stefania/Didattica/AA2013-2014/
ORGANIZZAZIONE DEL CORSO
INTEGRATO
INTRODUZIONE ALLA
BIOINFORMATICA
8 ore F
TEORIA INFORMATICA
16 ore F
LABORATORIO PRATICO
INFORMATICA
16 ore L
LABORATORIO PRATICO
BIOINFORMATICA
16 ore L
ORARIO E AULE ONLINE
TESTI e materiali CONSIGLIATI
INFORMATICA
• Colussi, File', Rossi, Informatica di base, Libreria
progetto, 2003.
• J. Glenn Brookshear (2006) Informatica: una
panoramica generale. Pearson/Addison Wesley.
(approfondimenti)
• Python:
http://www.python.it/doc/Howtothink/HowToThink_ITA.p
df
BIOINFORMATICA
• Materiale lezioni
• Risorse e tutorial online
• Per approfondimento facoltativo: Fondamenti di
Bioinformatica, Krane e Raymer, Pearson, 2007
THE BIG DATA ERA
“Researchers need
to be obliged to
document
and
manage their data
with
as
much
professionalism as
they devote to their
experiments.”
Nature journal Issue of 4 2008
 Importance of data:
• Retrieval
• Integration
• Analysis
 An at least basic knowledge of bioinformatic
methods in unavoidable also for experimental
researchers
 Bioinformatics
from basic methods for managing biosequences to
systems biology models
NIH BIG DATA to Knowledge (BD2K)
With advances in technologies,
investigators are increasingly
generating and using large,
complex, and diverse datasets.
Consequently, the biomedical
research
enterprise
is
increasingly becoming dataintensive and data-driven.
However, the ability of researchers to locate, analyze, and use Big Data (and
more generally all biomedical and behavioral data) is often limited for reasons
related to access to relevant software and tools, expertise, and other factors.
D2K aims to develop the new approaches, standards, methods, tools, software,
and competencies that will enhance the use of biomedical Big Data by
supporting research, implementation, and training in data science and other
Importance of Bioinformatics
Deep sequencing data analysis
DATABASES AND DATA RETRIEVAL
Biosequences and Gene-related info
WORKING WITH BIOSEQUENCES
Alignments and similarity search
NAVIGATING GENOMES
By Genome Browsers
gene details
official
sequence
Annotation Tracks
comparisons
SNPs
EXAMPLES FROM MORE ADVANCED
BIOINFORMATICS
Gene expression and RNA-seq data analysis
Opportunities and Challenges
 OPPORTUNITIES:
• estimate the odds of your
future children being born with
something like Down syndrome
• secure paternity test
• customized cancer-fighting
drugs
• personalized medicine
Opportunities and Challenges
 OPPORTUNITIES:
• estimate the odds of your
future children being born with
something like Down syndrome
• secure paternity test
• customized cancer-fighting
drugs
• personalized medicine
 CHALLENGES:
• do you have something more
“private” than your DNA?
• consumers fear losing
insurance coverage if results
are shared, companies don’t
want to reveal proprietary
information about customized
treatments
“When your bank account or
credit card is compromised,
the situation is painful but
recoverable. You can close the
account, wipe the slate clean
and start over.
You cannot change or revoke
your DNA once it’s leaked,”
says Gene Tsudik – UCI –
GenoDroid project.