Predicting the Metabolic Pathways of Small Molecules Based on Their Physicochemical Properties
Chun-Rong Peng, Wen-Cong Lu, Bing Niu, Min-Jie Li, Xiao-YanYang and Mi-Lin Wu
Affiliation: Department of Chemistry, College of Sciences, Shanghai University, 99 Shang-Da Road, Shanghai 200444, China.
How to correctly and efficiently map small molecule to its possible metabolic pathway is a meaningful topic to
metabonomics research. In this work, a novel approach to address this problem was introduced to encode physicochemical
properties of small molecules. Based on this encoding method, a two stage feature selection method called mRMR-FFSAdaBoost
was adopted to map small molecules to their corresponding metabolic pathways possible. As a result, the accuracies
of 10-folds cross-validation test and independent set test for predicting the metabolic pathways of small molecules
reached 83.88% and 85.23%, respectively. An online server for predicting metabolic pathways of unknown small molecules
as described in this paper is accessible at http://chemdata.shu.edu.cn:8080/PathwayPrediction/.
Keywords: ChemAxon, jchem for excel, KEGG, metabolic pathway, online server, small molecules, web-server, biochemical reactions, living systems, biological functions.
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