Abstract for talk at CCBR at U Toronto ((* i0tor12 *))

TITLE:

Molecular Networks: The Next-generation Annotation for Personal Genomes

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

Abstract for talk at Next Generation Sequencing for Drug Developers ((* i0ngenddev *))

TITLE:

Molecular Networks: The Next-generation Annotation for Personal Genomes

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

abstract for talk at Harvard Systems Biology [i0hsb]

TITLE:

Molecular Networks: The Next-generation Annotation for Personal Genomes

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

abstract for talk at UCLA [i0ucla]

TITLE:

Analysis of Molecular Networks

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

abstract for talk at CMU [i0cmu12]

TITLE:

Analysis of Molecular Networks

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

abstract for talk at UMD Center for Bioinformatics and Computational Biology [i0cbcb]

TITLE:

Analysis of Molecular Networks

Mark Gerstein

Yale University

My talk will be concerned the analysis of networks and the use of
networks as a "next-generation annotation" for interpreting personal
genomes. I will initially describe current approaches to genome
annotation in terms of one-dimension browser tracks. Then I will
describe various aspects of networks. In particular, I will touch on
the following topics: (1) I will show how analyzing the structure of
the regulatory network indicates that it has a hierarchical layout
with the "middle-managers" acting as information-flow bottlenecks and
with more "influential" TFs on top. (2) I will show that most human
variation occurs at the periphery of the network. (3) I will compare
the topology and variation of the regulatory network to the call graph
of a computer operating system, showing that they have different
patterns of variation. (4) I will talk about web-based tools for the
analysis of networks (TopNet and tYNA).

http://networks.gersteinlab.org
http://tyna.gersteinlab.org

Comparing genomes to computer operating systems in terms of the
topology and evolution of their regulatory control networks.
KK Yan, G Fang, N Bhardwaj, RP Alexander, M Gerstein (2010). Proc Natl
Acad Sci U S A 107:9186-91.

Analysis of diverse regulatory networks in a hierarchical context
shows consistent tendencies for collaboration in the middle levels.
N Bhardwaj, KK Yan, MB Gerstein (2010). Proc Natl Acad Sci U S A 107:6841-6.

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.

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.

abstract for talk at DOE Workshop ((* i0gtl2012 *))

Tools and Approaches for Integrating Multiple genetic and Cellular Networks

One important task of KBase is to provide a platform to help users
analyze gene biological function and inspire experiments for the
purpose of biofuel development. A gene's biological function is
essentially its relationships or interactions with other biological
objects within the cell and around the environment. It is necessary to
understand gene function on a genomic scale, and from the integration
of genetic and cellular networks. We approach this through the
prediction and analysis of biological networks, focusing on
protein-protein and transcription-factor-target interactions. We
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, we will report 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 allow them to act
as biosensors; (3) Analyzing the structure of the regulatory network
which indicates that it has a hierarchical layout with the
"middle-managers" acting as information bottlenecks; (4) Showing these
middle managers tend be arranged in various "partnership" structures
giving the hierarchy a "democratic character" ; (5) Comparing the
topology and variation of the regulatory network to the call graph of
a computer operating system; (6) Developing a framework to integrate
together various kinds of  biological networks (e.g. relating to TFs
and miRNAs) into an integrated meta-network; (7) Integrating this
meta-network with actual molecular structures; and (8) Creating
practical web-based tools for the analysis of these networks (DynaSIN
and tYNA).

http://www.orau.gov/gtl2012