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Predicting Gene Knockout Effects by Minimal Pathway Enumeration

Authors:
Takehide Soh
Katsumi Inoue
Tomoya Baba
Toyoyuki Takada
Toshihiko Shiroishi

Keywords: metabolic pathways; gene knockout; prediction method; minimal pathway; Keio collection.

Abstract:
In this paper, we propose a method to predict gene knockout effects for the cell growth by utilizing biological databases such as KEGG and EcoCyc, in which biological knowledge and experimental results have been collected. We construct biological networks from such databases and configure experimental conditions by giving source metabolites, target metabolites, and knockout genes. We then enumerate all minimal active pathways, which are minimal subsets of a given network using source metabolites to produce target metabolites. We simulate the effects of gene knockouts by measuring the difference of minimal active pathways between original networks and knockout ones. In the experiments, we applied it to predict the gene knockout effects on the glycolysis pathway of Escherichia coli. In the results, our method predicted three out of four essential genes, which are confirmed by the Keio collection containing comprehensive cell growth data obtained from biological experiments.

Pages: 11 to 19

Copyright: Copyright (c) IARIA, 2012

Publication date: March 25, 2012

Published in: conference

ISSN: 2308-4383

ISBN: 978-1-61208-190-8

Location: St. Maarten, The Netherlands Antilles

Dates: from March 25, 2012 to March 30, 2012