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Journal of Shanghai University >

2012 , Vol. 18 >Issue 3: 265 - 270

DOI: https://doi.org/10.3969/j.issn.1007-2861.2012.03.010

Mathematics.Physics and Chemistry

Prediction of ProteinProtein Interactions Based on Association Rule Mining

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  • (College of Sciences, Shanghai University, Shanghai 200444, China)

Online published: 2012-06-30

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Abstract

Association rule (AR) mining has been successfully applied to predict proteinprotein interactions (PPIs) through protein’s primary sequence. A conjoint triad feature is used to describe amino acids. Experimental results show that the proposed method can predict PPIs with high accuracy under different classifications of Cys. The predicted results of two classifications of Cys are compared.

Key words： association rule mining; classification of amino acids; proteinprotein interactions (PPIs); sequential coding

Cite this article

LIN He-tong,GONG Yun-lu,QIN Dian-gang,FENG Tie-nan,WANG Yi-fei . Prediction of ProteinProtein Interactions Based on Association Rule Mining[J]. Journal of Shanghai University, 2012 , 18(3) : 265 -270 . DOI: 10.3969/j.issn.1007-2861.2012.03.010

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