A supervised approach to detect protein complex by combining biological and topological properties. (1st January 2013)

• Record Type: Journal Article
• Authors: Yu, Yang; Wang, Xiaolong; Lin, Lei; Sun, Chengjie; Wang, Xuan
• Is Part Of: International journal of data mining and bioinformatics. Volume 8:Number 1(2013)
• Page Start: 105
• Page End: 121
• Publication Date: 2013-01-01
• Subjects: PPI -- protein-protein interaction -- protein complex detection -- amino acid background frequency -- SVM -- support vector machine; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

Protein biochemical functions are revealed in the form of protein complexes from the Protein-Protein Interaction (PPI) network. In this paper, we propose a supervised based algorithm by combining biological and topological properties to detect protein complexes in PPI networks, in which protein amino acid background frequency is introduced as biological properties and become a new block of the features. In comparison with other established methods, the evaluation results indicate that the applied method can achieve comparable performances and match more meaningful real complexes. We also demonstrate that the use of protein amino acid background frequency and the SVM based method can efficiently improve the performance.