Understanding Protein Function on a Genome-scale using Networks
Mark Gerstein
Yale University
My talk will be concerned with topics in proteomics, in particular
predicting protein function on a genomic scale. We approach 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 simple topological statistics. In particular, I will discuss a
number of specific analyses: (1) Integrating gene expression data with
the regulatory network illuminates transient hubs; (2) Integration of
the protein interaction network with 3D molecular structures reveals
different types of hubs, depending on the number of interfaces
involved in interactions (one or many); (3) Analysis of betweenness in
biological networks reveals that this quantity is more strongly
correlated with essentially than degree; (4) Analysis of structure of
the regulatory network shows that it has a hierarchiel layout with the
"middle-managers" acting as information bottlenecks. (5) Development
of a useful web-based tools for the analysis of networks, TopNet and
tYNA.
http://bioinfo.mbb.yale.edu
http://topnet.gersteinlab.org
Integrated prediction of the helical membrane protein interactome in
yeast. Y Xia, LJ Lu, M Gerstein (2006) J Mol Biol 357: 339-49.
Relating three-dimensional structures to protein networks provides
evolutionary insights. PM Kim, LJ Lu, Y Xia, MB Gerstein (2006)
Science 314: 1938-41.
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.
The importance of bottlenecks in protein networks: correlation with
gene essentiality and expression dynamics. H Yu, PM Kim, E Sprecher,
V Trifonov, M Gerstein (2007) PLoS Comput Biol 3: e59.
Genomic analysis of the hierarchical structure of regulatory networks.
H Yu, M Gerstein (2006) Proc Natl Acad Sci U S A 103: 14724-31.
The role of disorder in interaction networks: a structural analysis.
PM Kim, A Sboner, Y Xia, M Gerstein (2008) Mol Syst Biol 4: 179.
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.
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