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A nearest neighbor algorithm based predictor for the prediction of enzyme-small molecule interaction.
Hu, Le-Le; He, Zhi-Song; Shi, Xiao-He; Kong, Xiang-Ying; Li, Hai-Peng; Lu, Wen-Cong.
Afiliação
  • Hu LL; Department of Chemistry, College of Sciences, Shanghai University, Shanghai, China.
Protein Pept Lett ; 19(1): 91-8, 2012 Jan.
Article em En | MEDLINE | ID: mdl-21919855
ABSTRACT
It is of great use to find out and clear up the interactions between enzymes and small molecules, for understanding the molecular and cellular functions of organisms. In this study, we developed a novel method for the prediction of enzyme-small molecules interactions based on machine learning approach. The biochemical and physicochemical description of proteins and the functional group composition of small molecules are used for representing enzyme-small molecules pairs. Tested by jackknife cross-validation, our predictor achieved an overall accuracy of 87.47%, showing an acceptable efficiency. The 39 features selected by feature selection were analyzed for further understanding of enzyme-small molecule interactions.
Assuntos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Proteínas / Análise de Sequência de Proteína / Bibliotecas de Moléculas Pequenas / Máquina de Vetores de Suporte Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Protein Pept Lett Ano de publicação: 2012 Tipo de documento: Article
Buscar no Google
Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Proteínas / Análise de Sequência de Proteína / Bibliotecas de Moléculas Pequenas / Máquina de Vetores de Suporte Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Protein Pept Lett Ano de publicação: 2012 Tipo de documento: Article