Abstract for nyas nyas-20060126

See http://www.nyas.org/ebrief/miniEB.asp?ebriefID=559
for an e-briefing

Title: Human Genome Annotation

A central problem for 21st century science will be the analysis and understanding of the human genome. My talk will be concerned with topics within this area, in particular annotating pseudogenes (protein fossils) in the genome. I will discuss a comprehensive pseudogene identification pipeline and storage database we have built. This has enabled use to identify >10K pseudogenes in the human and mouse genomes and analyze their distribution with respect to age, protein family, and chromosomal location. One interesting finding is the large number of ribosomal pseudogenes in the human genome, with 80 functional ribosomal proteins giving rise to ~2,000 ribosomal protein pseudogenes. I will try to inter-relate our studies on pseudogenes with those on tiling arrays, which enable one to comprehensively probe the activity of intergenic regions. At the end I will bring these together, trying to assess the transcriptional activity of pseudogenes. Throughout I will try to introduce some of the computational algorithms and approaches that are required for genome annotation and tiling arrays -- i.e. the construction of annotation pipelines, developing algorithms for optimal tiling, and refining approaches for scoring microarrays.

http://bioinfo.mbb.yale.edu
http://pseudogene.org
http://tiling.gersteinlab.org

Comparative analysis of processed pseudogenes in the mouse and human genomes. Z Zhang, N Carriero, M Gerstein (2004) Trends Genet 20: 62-7. Millions of years of evolution preserved: a comprehensive catalog of the processed pseudogenes in the human genome. Z Zhang, PM Harrison, Y Liu, M Gerstein (2003) Genome Res 13: 2541-58. Patterns of nucleotide substitution, insertion and deletion in the human genome inferred from pseudogenes. Z Zhang, M Gerstein (2003) Nucleic Acids Res 31: 5338-48. Integrated pseudogene annotation for human chromosome 22: evidence for transcription. D Zheng, Z Zhang, PM Harrison, J Karro, N Carriero, M Gerstein (2005) J Mol Biol 349: 27-45. P. Bertone, F. Schubert, V. Trifonov, J. Rozowsky, O. Emanuelsson, J. Karro, M-Y Kao, M. Snyder, M. Gerstein. Design optimization methods for genomic DNA tiling arrays. Genome Research (in press). TE Royce, JS Rozowsky, P Bertone, M Samanta, V Stolc, S Weissman, M Snyder, M Gerstein (2005). "Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping." Trends Genet 21: 466-75.

Abstract for orfeome06-20061116

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.

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.