Bio-informatic approach to genetic networks

Bio-informatic approach to genetic networks

Coordinator: Hao Li (UCSF)

The aim of this mini-workshop is to bring together experts in the field of bio-informatics to discuss current challenges and opportunities. In particular the program will focus on the possible lines of attack for unraveling of the complex structure of genetic networks.
Complete genome sequences of multiple species and systematic gene expression and protein-protein interaction data open up new, bio-informatic, routes for discovering and ‘reverse-engineering’ regulatory links, their effects and interactions. These “high-throughput” data driven approaches may be able to greatly enhance, supplement and perhaps sometimes replace more traditional genetic methods of mapping regulatory and control pathways. The time is ripe now for a systematic effort to map the connections of the networks on a genomic scale.

The following are a partial list of possible subjects for discussion.
1) Using comparative genomics approach to identify conserved pathways and species specific innovations. Analyzing the dynamic responses of similar pathways in different organisms.
2) Predicting protein-protein interaction patterns and binding interfaces. Protein domain classification and signal integration by protein domains.
3) Deciphering the regulatory programs encoded in genome sequences.
4) Combinatorial control of gene regulation and cross talks between pathways.
5) Statistical inference of network structure using gene expression and protein/protein and protein/DNA interaction data.

Preliminary Schedule:

Mon 2/24 Tue 2/25 Wed 2/26 Thu 2/27 Fri 2/28

9:00-10:00am J. DeRisi (UCSF)
E. Koonin (NIH) G. Stormo (WU) M. Zhang (CSHL)
T. Hwa (UCSD)

Genomics and Infectious Disease

Birth and death of domains: Simple models of genome evolution explain power law distribution of protein family size

Prospects for a useful protein-DNA recognition code
Computational Molecular Biology of Gene Expression and Regulation
The style of genetic computing

10:00-10:30am Break Break Break Break Break

10:30-11:30am E. Siggia (Rockefeller) S. Tavazoie (Princeton)
B. Ren (UCSD)
Hao Li (UCSF) H. Bussemaker (Columbia)

Analysis of regulatory sequence in bacteria, yeast and fly
From DNA sequence to gene expression
Dissecting the Myc regulation network using promoter microarrays
Reconstructing the transcription networks of a cell using computational genomics
Using regression analysis to infer regulatory circuitry from genome-wide gene expression and binding data

11:30-12:30pm Discussion
A.Sengupta (Rutgers)
D. Haynor (U. Washington)
Discussion
Discussion

Biophysical approach to transcription factor binding site discovery
Computational modeling of the yeast transcriptional network

12:30pm
Lunch
Lunch
Lunch
Lunch
Lunch

5:30pm
Wine&Beer

Dinner in SB

	Mon 2/24	Tue 2/25	Wed 2/26	Thu 2/27	Fri 2/28
9:00-10:00am	J. DeRisi (UCSF)	E. Koonin (NIH)	G. Stormo (WU)	M. Zhang (CSHL)	T. Hwa (UCSD)
	Genomics and Infectious Disease	Birth and death of domains: Simple models of genome evolution explain power law distribution of protein family size	Prospects for a useful protein-DNA recognition code	Computational Molecular Biology of Gene Expression and Regulation	The style of genetic computing
10:00-10:30am	Break	Break	Break	Break	Break
10:30-11:30am	E. Siggia (Rockefeller)	S. Tavazoie (Princeton)	B. Ren (UCSD)	Hao Li (UCSF)	H. Bussemaker (Columbia)
	Analysis of regulatory sequence in bacteria, yeast and fly	From DNA sequence to gene expression	Dissecting the Myc regulation network using promoter microarrays	Reconstructing the transcription networks of a cell using computational genomics	Using regression analysis to infer regulatory circuitry from genome-wide gene expression and binding data
11:30-12:30pm	Discussion	A.Sengupta (Rutgers)	D. Haynor (U. Washington)	Discussion	Discussion
		Biophysical approach to transcription factor binding site discovery	Computational modeling of the yeast transcriptional network
12:30pm	Lunch	Lunch	Lunch	Lunch	Lunch
5:30pm	Wine&Beer		Dinner in SB