Abstract
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.
Protein & Peptide Letters
Title:Predicting the Metabolic Pathways of Small Molecules Based on Their Physicochemical Properties
Volume: 19 Issue: 12
Author(s): Chun-Rong Peng, Wen-Cong Lu, Bing Niu, Min-Jie Li, Xiao-YanYang and Mi-Lin Wu
Affiliation:
Keywords: ChemAxon, jchem for excel, KEGG, metabolic pathway, online server, small molecules, web-server, biochemical reactions, living systems, biological functions.
Abstract: 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/.
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Cite this article as:
Peng Chun-Rong, Lu Wen-Cong, Niu Bing, Li Min-Jie, Xiao-YanYang and Wu Mi-Lin, Predicting the Metabolic Pathways of Small Molecules Based on Their Physicochemical Properties, Protein & Peptide Letters 2012; 19 (12) . https://dx.doi.org/10.2174/092986612803521585
DOI https://dx.doi.org/10.2174/092986612803521585 |
Print ISSN 0929-8665 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5305 |
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