Modeling of biological genetic networks forms the basis of systems biology. In this paper, we present an optimization-based inference scheme to identify temporally evolving Boolean network representations of genetic networks from data. In the formulation of the optimization problem, we use an adjacency map as a priori information, and define a cost function which both drives the connectivity of the graph to match biological data as well as generates a sparse and robust network at corresponding time intervals. Throughout simulation studies on simple examples, it is shown that this optimization scheme can help to understand the structure and dynamics of biological genetic networks.
Title
Optimization-based Inference for Temporally Evolving Boolean Networks with Applications in Biology
Published
2010-10-26
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
EECS-2010-133
Type
Text
Extent
10 p
Archive
The Engineering Library
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