Monday, February 23, 2009

abstract for talk at Sarkar Lecture in Toronto on 29-Apr-2009 [I:SARKAR]

Title: Human Genome Annotation

A central problem for 21st century science will be the annotation and
understanding of the human genome. My talk will be concerned with
topics within this area, in particular annotating pseudogenes (protein
fossils), binding sites, CNVs, and novel transcribed regions in the
genome. Much of this work has been carried out in the framework of the
ENCODE and modENCODE projects.

In particular, I will discuss how we identify regulatory regions and
novel, non-genic transcribed regions in the genome based on processing
of tiling array and next-generation sequencing experiments. I will
further discuss how we cluster together groups of binding sites and
novel transcribed regions.

Next, I will discuss a comprehensive pseudogene identification
pipeline and storage database we have built. This has enabled us to
identify >10K pseudogenes in the human and mouse genomes and analyze
their distribution with respect to age, protein family, and
chromosomal location. I will try to inter-relate our studies on
pseudogenes with those on transcribed 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 --
e.g., 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 ribosomal protein pseudogenes in four
mammalian genomes.
S Balasubramanian, D Zheng, YJ Liu, G Fang, A Frankish, N Carriero, R
Robilotto, P Cayting, M Gerstein (2009) Genome Biol 10: R2.

Pseudogenes in the ENCODE regions: consensus annotation, analysis of
transcription, and evolution.
D Zheng, A Frankish, R Baertsch, P Kapranov, A Reymond, SW Choo, Y Lu, F
Denoeud, SE Antonarakis, M Snyder, Y Ruan, CL Wei, TR Gingeras, R Guigo,
J Harrow, MB Gerstein (2007) Genome Res 17: 839-51.

Statistical analysis of the genomic distribution and correlation of
regulatory
elements in the ENCODE regions.
ZD Zhang, A Paccanaro, Y Fu, S Weissman, Z Weng, J Chang, M Snyder, MB
Gerstein
(2007) Genome Res 17: 787-97.

What is a gene, post-ENCODE? History and updated definition.
MB Gerstein, C Bruce, JS Rozowsky, D Zheng, J Du, JO Korbel, O
Emanuelsson, ZD
Zhang, S Weissman, M Snyder (2007) Genome Res 17: 669-81.

PeakSeq enables systematic scoring of ChIP-seq experiments relative to
controls.
J Rozowsky, G Euskirchen, RK Auerbach, ZD Zhang, T Gibson, R
Bjornson, N Carriero, M Snyder, MB Gerstein (2009) Nat Biotechnol

MSB: A mean-shift-based approach for the analysis of structural
variation in the genome.
LY Wang, A Abyzov, JO Korbel, M Snyder, M Gerstein (2009) Genome
Res 19: 106-17.

Pseudofam: the pseudogene families database.
HY Lam, E Khurana, G Fang, P Cayting, N Carriero, KH Cheung, MB
Gerstein (2009) Nucleic Acids Res 37: D738-43.


Analysis of copy number variants and segmental duplications in the human
genome: Evidence for a change in the process of formation in recent
evolutionary history.
PM Kim, HY Lam, AE Urban, JO Korbel, J Affourtit, F Grubert, X
Chen, S Weissman, M Snyder, MB Gerstein (2008) Genome Res 18: 1865-74.

Sunday, February 8, 2009

abstract for talk at CSHL on 29-Apr-2009 [I:CSHL]

Title: Human Genome Annotation

A central problem for 21st century science will be the annotation and
understanding of the human genome. My talk will be concerned with
topics within this area, in particular annotating pseudogenes (protein
fossils), binding sites, CNVs, and novel transcribed regions in the
genome. Much of this work has been carried out in the framework of the
ENCODE and modENCODE projects.

In particular, I will discuss how we identify regulatory regions and
novel, non-genic transcribed regions in the genome based on processing
of tiling array and next-generation sequencing experiments. I will
further discuss how we cluster together groups of binding sites and
novel transcribed regions.

Next, I will discuss a comprehensive pseudogene identification
pipeline and storage database we have built. This has enabled us to
identify >10K pseudogenes in the human and mouse genomes and analyze
their distribution with respect to age, protein family, and
chromosomal location. I will try to inter-relate our studies on
pseudogenes with those on transcribed 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 --
e.g., 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

Toward a universal microarray: prediction of gene expression through
nearest-neighbor probe sequence identification.
TE Royce, JS Rozowsky, MB Gerstein (2007) Nucleic Acids Res 35: e99.

Pseudogenes in the ENCODE regions: consensus annotation, analysis of
transcription, and evolution.
D Zheng, A Frankish, R Baertsch, P Kapranov, A Reymond, SW Choo, Y Lu, F
Denoeud, SE Antonarakis, M Snyder, Y Ruan, CL Wei, TR Gingeras, R Guigo, J
Harrow, MB Gerstein (2007) Genome Res 17: 839-51.

Statistical analysis of the genomic distribution and correlation of
regulatory
elements in the ENCODE regions.
ZD Zhang, A Paccanaro, Y Fu, S Weissman, Z Weng, J Chang, M Snyder, MB
Gerstein
(2007) Genome Res 17: 787-97.

What is a gene, post-ENCODE? History and updated definition.
MB Gerstein, C Bruce, JS Rozowsky, D Zheng, J Du, JO Korbel, O
Emanuelsson, ZD
Zhang, S Weissman, M Snyder (2007) Genome Res 17: 669-81.

PeakSeq enables systematic scoring of ChIP-seq experiments relative to
controls.
J Rozowsky, G Euskirchen, RK Auerbach, ZD Zhang, T Gibson, R
Bjornson, N Carriero, M Snyder, MB Gerstein (2009) Nat Biotechnol

MSB: A mean-shift-based approach for the analysis of structural
variation in the genome.
LY Wang, A Abyzov, JO Korbel, M Snyder, M Gerstein (2009) Genome
Res 19: 106-17.

Pseudofam: the pseudogene families database.
HY Lam, E Khurana, G Fang, P Cayting, N Carriero, KH Cheung, MB
Gerstein (2009) Nucleic Acids Res 37: D738-43.


Analysis of copy number variants and segmental duplications in the human
genome: Evidence for a change in the process of formation in recent
evolutionary history.
PM Kim, HY Lam, AE Urban, JO Korbel, J Affourtit, F Grubert, X
Chen, S Weissman, M Snyder, MB Gerstein (2008) Genome Res 18: 1865-74.

Sunday, February 1, 2009

Abstract 305094 for talk at JSM 2009 3-Aug-09 [I:JSM]

Abstract Number 305094 has been submitted.


Abstract Information
*Abstract Type:* Topic Contributed
*Sub Type:* Papers
*Sponsor:* Biometrics Section

*Title:* Understanding Protein Function on a Genome-scale using Networks

*Abstract:* My talk will be concerned with understanding 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 genomic features and how they
can be analyzed in terms of various topological statistics. In
particular, I will discuss: (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; (3) analyzing the structure of regulatory networks shows
they have hierarchical layouts with "middle-managers" acting as
information bottlenecks. [REFS: K Yip & M Gerstein ('09) Bioinformatics
25:243; T Gianoulis et al ('09) PNAS 16:1374; Networks.GersteinLab.org]

*Key words:* bioinformatics, network, training set, metagenomics, cca,
integration