TY - GEN
T1 - Optimization-based inference for temporally evolving Boolean networks with applications in biology
AU - Chang, Young Hwan
AU - Gray, Joe
AU - Tomlin, Claire
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=80053158755&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053158755&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80053158755
SN - 9781457700804
T3 - Proceedings of the American Control Conference
SP - 4129
EP - 4134
BT - Proceedings of the 2011 American Control Conference, ACC 2011
T2 - 2011 American Control Conference, ACC 2011
Y2 - 29 June 2011 through 1 July 2011
ER -