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
at the periphery of the protein interaction network; (5) Comparing the
topology and variation of the regulatory network to the call graph of
a computer operating system; and (5) Developing useful web-based tools
for the analysis of networks (TopNet and tYNA).
http://networks.gersteinlab.org
http://topnet.gersteinlab.org
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)
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 Gianoulis, J Raes, P Patel, R Bjornson, J Korbel, I Letunic, T
Yamada, A Paccanaro, L Jensen, M Snyder, P Bork, M Gerstein (2009)
PNAS
Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010) Proc Natl
Acad Sci U S A
