Friday, January 16, 2009

Re: abstract for talk at National Academy of Engineering meeting at Columbia on 14-Apr-2009 [I:NAECU]

Mark: I am impressed by your research depth and prowess. For the NAE
audience, communication is most important....not necessary the details
of a research presentation. Most of the audience are quite senior and
you will need to reach them and capture their attention.

Looking forward to meeting you in April. For your travel expenses,
including an over night stay in Manhattan if you prefer, please let my
assistant Ms. Paulette Louissaint know of your needs. Keep all expense
receipts. If you are staying overnight, we can plan for a dinner
together and arrange you accommodations. The details of the day's
activities will be formulated soon. Thanking you again to share you
time and expertise. Regards, Van Mow


Mark Gerstein wrote:
> TITLE:
>
> Understanding Protein Function on a Genome-scale using Networks
>
> Mark Gerstein
>
> Yale University
>
> My talk will be concerned with understanding protein function on a
> genomic scale. My lab approaches 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 topological
> statistics. In particular, I will discuss a number of recent analyses:
> (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)
> Showing how integrating gene expression data with regulatory networks
> identifies transient hubs for characterizing of proteins of unknown
> function; (4) Analyzing the structure of the regulatory network shows
> that it has a hierarchical layout with the "middle-managers" acting as
> information bottlenecks; (5) Showing that most human variation occurs
> on the periphery of the protein interaction network; and (6)
> Developing useful web-based tools for the analysis of networks (TopNet
> and tYNA).
>
> http://networks.gersteinlab.org
> http://topnet.gersteinlab.org
>
> 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.
>
> Genomic analysis of the hierarchical structure of regulatory networks.
> H Yu, M Gerstein (2006) Proc Natl Acad Sci U S A 103: 14724-31.
>
> 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.
>
> Training Set Expansion: An Approach to Improving the Reconstruction of
> Biological Networks from Limited and Uneven Reliable Interactions. KY
> Yip, M Gerstein (2008) Bioinformatics (in press)
>
> Quantifying environmental adaptation of metabolic pathways in
> metagenomics T Gianoulisa, J Raes, P Patel, R Bjornson, J Korbel, I
> Letunic, T Yamada, A Paccanaro, L Jensen, M Snyder, P Bork, M Gerstein
> (2009) PNAS (in press)
>
> 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.
>
>
>
>

Thursday, January 15, 2009

abstract for talk at National Academy of Engineering meeting at Columbia on 14-Apr-2009 [I:NAECU]

TITLE:

Understanding Protein Function on a Genome-scale using Networks

Mark Gerstein

Yale University

My talk will be concerned with understanding protein function on a
genomic scale. My lab approaches 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 topological
statistics. In particular, I will discuss a number of recent analyses:
(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)
Showing how integrating gene expression data with regulatory networks
identifies transient hubs for characterizing of proteins of unknown
function; (4) Analyzing the structure of the regulatory network shows
that it has a hierarchical layout with the "middle-managers" acting as
information bottlenecks; (5) Showing that most human variation occurs
on the periphery of the protein interaction network; and (6)
Developing useful web-based tools for the analysis of networks (TopNet
and tYNA).

http://networks.gersteinlab.org
http://topnet.gersteinlab.org

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.

Genomic analysis of the hierarchical structure of regulatory networks.
H Yu, M Gerstein (2006) Proc Natl Acad Sci U S A 103: 14724-31.

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.

Training Set Expansion: An Approach to Improving the Reconstruction of
Biological Networks from Limited and Uneven Reliable Interactions. KY
Yip, M Gerstein (2008) Bioinformatics (in press)

Quantifying environmental adaptation of metabolic pathways in
metagenomics T Gianoulisa, J Raes, P Patel, R Bjornson, J Korbel, I
Letunic, T Yamada, A Paccanaro, L Jensen, M Snyder, P Bork, M Gerstein
(2009) PNAS (in press)

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.