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2009 IEEE International Conference on Bioinformatics and Biomedicine
Side Effect Prediction Using Cooperative Pathways
Washington, D.C., USA
November 01-November 04
ISBN: 978-0-7695-3885-3
Drugs and biological experiments are designed to affect a particular target gene or pathway. However, they might inadvertently activate other pathways and cause side effects.Because of the existence of complex cellular mechanisms responding to stimuli,it is difficult to detect the presence of such side effects.Therefore, identification of pathways that function together under identical conditions would greatly help in anticipating these side effects before conducting these experiments. We develop a novel method to enumerate ``cooperative pathways'' defined as pathways that functiontogether under identical conditionsby combining pathway networks withcomprehensive gene expression profiles.For finding cooperative pathways from whole pathways,we propose an efficient algorithm, CoopeRativE Pathway Enumerator (CREPE),which enumerates connected subpathways having common activate conditionsand selects combinations of the subpathways sharing the conditions.%We apply CREPE to a yeast stress dataset combined with the KEGG pathways.We observe that the starch and sucrose metabolism pathwaycooperates with the pyruvate metabolism under heat shock stresses. It cooperates with the tricarboxylic acid (TCA) cycle under the stationary phases.
Index Terms:
gene expression, side effect, pathway, active network, itemset
Citation:
Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese, "Side Effect Prediction Using Cooperative Pathways," bibm, pp.142-147, 2009 IEEE International Conference on Bioinformatics and Biomedicine, 2009
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