Sunday, May 20, 2007

Abstract for talk [I] at Brown


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.

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
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.

Relating three-dimensional structures to protein networks provides evolutionary
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.

-- * 203 432-6105 *

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