Prediction of protein-protein interacting sites by combining SVM algorithm with bayesian method

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - Third International Conference on Natural Computation, ICNC 2007
Pages329-333
Volume2
Publication statusPublished - 2007

Publication series

Name
Volume2

Conference

Title3rd International Conference on Natural Computation, ICNC 2007
PlaceChina
CityHaikou, Hainan
Period24 - 27 August 2007

Abstract

The ability to identity protein-protein binding sites has important implications for drug design and understanding cell activity. This paper presents a method that can predict protein binding sites of transient protein-protein interactions using protein residue conservation and evolution information, i.e., spatial sequence profile, sequence information entropy and evolution rate. A two-stage predictor is constructed to predict surface residues are participated into protein-protein interface. The first stage consists of three predictors based on support vector machines (SVM) algorithm. Bayesian discrimination is used at the second stage by considering the predicted labels of spatial neighbor residues. The improvement of prediction performances exploits that binding site tend to form spatial cluster. Our proposed approach is promising which can be verified by its better prediction performance based on a non-redundant data set of transient protein-protein heterodimers. © 2007 IEEE.

Citation Format(s)

Prediction of protein-protein interacting sites by combining SVM algorithm with bayesian method. / Wang, Bing; Ge, Lu Sheng; Huang, De-Shuang et al.
Proceedings - Third International Conference on Natural Computation, ICNC 2007. Vol. 2 2007. p. 329-333 4304572.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review