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- W2385057332 abstract "The problem of identifying dynamics of biological networks is of critical importance in order to understand biological systems. In this article, we propose a data-driven inference scheme to identify temporally evolving network representations of genetic networks. In the formulation of the optimization problem, we use an adjacency map as a priori information and define a cost function that both drives the connectivity of the graph to match biological data as well as generates a sparse and robust network at corresponding time intervals. Through simulation studies of simple examples, it is shown that this optimization scheme can help capture the topological change of a biological signaling pathway, and furthermore, might help to understand the structure and dynamics of biological genetic networks." @default.
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- W2385057332 date "2012-12-01" @default.
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- W2385057332 title "Optimization-based Inference for Temporally Evolving Networks with Applications in Biology" @default.
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- W2385057332 doi "https://doi.org/10.1089/cmb.2012.0190" @default.
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