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).
Saturday, February 25, 2012
abstract for talk at DOE Workshop ((* i0gtl2012 *))
Tools and Approaches for Integrating Multiple genetic and Cellular Networks
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