Saturday, March 27, 2010

abstract for talk at Brown Appl. Math 9 apr 2010 [I:BROWNMATH]


Analysis of Molecular Networks

Mark Gerstein

Yale University

My talk will be concerned with understanding protein function on a
genomic scale. My lab approaches this through the prediction and
analysis of biological networks, focusing on protein-protein
interaction and transcription-factor-target ones. I will describe how
these networks can be determined through integration of many genomic
features and how they can be analyzed in terms of various topological
statistics. In particular, I will discuss a number of recent analyses:
(1) Improving the prediction of molecular networks through systematic
training-set expansion; (2) Showing how the analysis of pathways
across environments potentially allows them to act as biosensors; (3a)
Analyzing the structure of the regulatory network indicates that it
has a hierarchical layout with the "middle-managers" acting as
information bottlenecks; (3b) Showing these middle managers tend be
arranged in various "partnership" structures giving the hierarchy a
"democratic character" ; (4) Showing that most human variation occurs
on the periphery of the protein interaction network; and (5)
Developing useful web-based tools for the analysis of networks (TopNet
and tYNA).

The tYNA platform for comparative interactomics: a web tool for
managing, comparing and mining multiple networks. KY Yip, H Yu, PM
Kim, M Schultz, M Gerstein (2006) Bioinformatics 22: 2968-70.

Analysis of Diverse Regulatory Networks in a Hierarchical Context:
Consistent Tendencies for Collaboration in the Middle Levels
N Bhardwaj et al. PNAS (2010, in press)

Positive selection at the protein network periphery: evaluation in
terms of structural constraints and cellular context. PM Kim, JO
Korbel, MB Gerstein (2007) Proc Natl Acad Sci U S A 104: 20274-9.

Training Set Expansion: An Approach to Improving the Reconstruction of
Biological Networks from Limited and Uneven Reliable Interactions. KY
Yip, M Gerstein (2008) Bioinformatics

Quantifying environmental adaptation of metabolic pathways in
metagenomics T Gianoulisa, J Raes, P Patel, R Bjornson, J Korbel, I
Letunic, T Yamada, A Paccanaro, L Jensen, M Snyder, P Bork, M Gerstein
(2009) PNAS

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