{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T18:44:43Z","timestamp":1777488283628,"version":"3.51.4"},"reference-count":20,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2009,4]]},"abstract":"<jats:p> 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\u2013protein 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. <\/jats:p>","DOI":"10.1142\/s0219720009004138","type":"journal-article","created":{"date-parts":[[2009,3,31]],"date-time":"2009-03-31T03:27:43Z","timestamp":1238470063000},"page":"309-322","source":"Crossref","is-referenced-by-count":20,"title":["AUTOMATIC MODELING OF SIGNALING PATHWAYS BY NETWORK FLOW MODEL"],"prefix":"10.1142","volume":"07","author":[{"given":"XING-MING","family":"ZHAO","sequence":"first","affiliation":[{"name":"Institute of Systems Biology, Shanghai University, Shanghai 200444, China"},{"name":"ERATO Aihara Complexity Modeling Project, JST, Tokyo 151-0064, Japan"},{"name":"Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, 230031, China"},{"name":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"RUI-SHENG","family":"WANG","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"LUONAN","family":"CHEN","sequence":"additional","affiliation":[{"name":"Institute of Systems Biology, Shanghai University, Shanghai 200444, China"},{"name":"ERATO Aihara Complexity Modeling Project, JST, Tokyo 151-0064, Japan"},{"name":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"},{"name":"Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"KAZUYUKI","family":"AIHARA","sequence":"additional","affiliation":[{"name":"Institute of Systems Biology, Shanghai University, Shanghai 200444, China"},{"name":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1089\/cmb.2006.13.133"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-3-34"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-5-158"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1002\/bit.21317"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-8-335"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkn145"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1038\/nbt924"},{"key":"rf10","doi-asserted-by":"publisher","DOI":"10.1038\/nature750"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0409522102"},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg239"},{"key":"rf13","first-page":"19","volume":"1725","author":"Tobias H.","journal-title":"Biochem. 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