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Keynote Speaker: Mark Gerstein, Yale University

Analysis of Molecular Networks

 

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 at the periphery of the protein interaction network;

(5a) Comparing the topology and variation of the regulatory network to the call graph of a computer operating system; and

(5b) Developing useful web-based tools for the analysis of networks (TopNet and tYNA).

More information is available at:
http://networks.gersteinlab.org
http://topnet.gersteinlab.org