Abstract for talk [I] at ENAR

TITLE:

Understanding Protein Function on a Genome-scale using Networks

Mark Gerstein

N Luscombe, Y Xia, H Yu, R Jansen, L Lu, Y Yip, P Kim, S Douglas, A Paccnarro

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 -- both of protein-protein interactions and transcription-factor-target relationships. 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. I will
discuss the accuracy of various reconstructed quantities.

http://bioinfo.mbb.yale.edu
http://topnet.gersteinlab.org

TopNet: a tool for comparing biological sub-networks, correlating protein properties with topological statistics.
H Yu, X Zhu, D Greenbaum, J Karro, M Gerstein (2004) Nucleic Acids Res 32: 328-37.

Genomic analysis of regulatory network dynamics reveals large topological changes.
NM Luscombe, MM Babu, H Yu, M Snyder, SA Teichmann, M Gerstein (2004) Nature 431: 308-12.

Annotation transfer between genomes: protein-protein interologs and protein-DNA
regulogs.
H Yu, NM Luscombe, HX Lu, X Zhu, Y Xia, JD Han, N Bertin, S Chung, M Vidal, M Gerstein (2004) Genome Res 14: 1107-18.

Genomic analysis of the hierarchical structure of regulatory networks.
H Yu, M Gerstein (2006) Proc Natl Acad Sci U S A

Integrated prediction of the helical membrane protein interactome in yeast.
Y Xia, LJ Lu, M Gerstein (2006) J Mol Biol 357: 339-49.