Statistical analysis applied to genome
and proteome analyses

Schedule and teachers

Location: rooms INR219 (theory) and INN218 (exercises)
Informatics Dept., EPFL, Lausanne

Time Topic Teacher
Mo Feb 04 DAY 1  
08:45 - 09:00 Welcome 
Laurent Falquet
09:00 - 12:30 Theory
- Differential gene expression, power and linear models.
- Exploratory unsupervised analyis.

Mauro Delorenzi
13:30-17:30 Exercises
Computer Lab with R.
Review: use of R
Case study PCA and clustering

Mauro Delorenzi
Eugenia Migliavacca
Thierry Sengstag
Tu Feb 05 DAY 2  
08:30 - 12:00 Theory
- Class discrimination for microarray studies.
- Analysis of multiple datasets and public databases.

Vlad Popovici

Pratyaksha Wirapati
13:30-17:30 Exercises
Computer Lab with R
Case study on Predictive gene signatures

Vlad Popovici
Pratyaksha Wirapati
Nadine Zangger
19:30 Social Dinner (map)
We Feb 06 DAY 3  
09:30 - 10:20 USGEB plenary session: 

Evolution of Cooperation in Ant and Robot Societies
Room SG1

L. Keller (UNIL-CH)
11:00 - 12:30 Theory
From Singular Value Decomposition to modular analysis of gene expression data

Sven Bergmann
13:30-14:45 Exercises
Computer Lab to modular analysis

Sven Bergmann
Bastian Peter
Gabor Csardi
15:00 - 16:15 USGEB plenary session: 

Designing Biological Systems

Robustness And Scaling In Developmental Patterning
Room SG1

P. Silver (Harvard Med. School, USA)
N. Barkai (Weizmann Inst., Israel)
16:30-17:30

Free time*


Th Feb 07 DAY 4  
09:00 - 10:15 USGEB plenary session: 

Studying Biomechanics To Gain Insight Into Sensory Perception

Lymphatic Biology And Interstitial Flow: Roles In Cancer Metastasis And Immunity
Room SG1

M. Hartmann (Northwestern U.-USA)

M. Swartz (EPFL-CH)
11:00 - 12:30 Theory
Genetic association studies: Introduction to the analysis of whole-genome SNP-array data

Sven Bergmann
13:30-14:45 Exercises
Computer Lab to Genetic association studies

Toby Johnson
Zoltán Kutalik
Alain Sewer
15:00 - 16:15 USGEB plenary session: 

Quantify What Cannot Be Measured: Small Molecule Fluxes Through Metabolic Networks

Biology As Reverse Engineering: A Few Examples
Room SG1

U. Sauer (ETHZ-CH)


S. Leibler (The Rockefeller U.-USA)

16:30-17:30

Free time*


Fr Feb 08 DAY 5  
08:30 - 12:00 Theory
Motif identification with position dependent weight matrix Estimating background models and score distributions

Félix Naef
13:30-15:30 Exercises
Computer Lab with R

Félix Naef
Guillaume Rey
Bernhard Sonderegger
16:00-17:30

Free time*

End of the course. Farewell.


* Time is given to the participants to finish their exercises, complete their reports or analyze their own data in the computer room