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- Title
Automatic modeling of signaling pathways by network flow model.
- Authors
Zhao, Xing-Ming; Wang, Rui-Sheng; Chen, Luonan; Aihara, Kazuyuki
- Abstract
Signal transduction is an important process that controls cell proliferation, metabolism, differentiation, and so on. Effective computational models which unravel such a process by taking advantage of high-throughput genomic and proteomic data are highly demanded to understand the essential mechanisms underlying signal transduction. Since protein-protein interaction (PPI) plays an important role in signal transduction, in this paper, we present a novel method for modeling signaling pathways from PPI networks automatically. Given an undirected weighted protein interaction network, finding signaling pathways is treated as searching for optimal subnetworks according to some cost function. To cope with this optimization problem, a network flow model is proposed in this work to extract signaling pathways from protein interaction networks. In particular, the network flow model is formalized and solved as a mixed integer linear programming (MILP) model, which is simple in algorithm and efficient in computation. The numerical results on two known yeast MAPK signaling pathways demonstrate the efficiency and effectiveness of the proposed method.
- Publication
Journal of bioinformatics and computational biology, 2009, Vol 7, Issue 2, p309
- ISSN
0219-7200
- Publication type
Journal Article
- DOI
10.1142/s0219720009004138