title: Prediction of protein-protein interactions based on feature selection and data balancing.
abstract: Computational approaches are able to analyze protein-protein interactions (PPIs) from a different angle of view by complementing the experimental ones. And they are very efficient in determining whether two proteins can interact with each other. In this paper, KNNs (K-nearest neighbors) is applied to predict the PPIs by coding each protein with the physical and chemical properties of its residues, predicted secondary structures and amino acid compositions. mRMR (minimum-redundancy maximum-relevance) feature selection is adopted to select a compact feature set, features of which are considered to be important for the determination of PPI-nesses. Because the size of the negative dataset (containing non-interactive protein pairs) is much larger than that of the positive dataset (containing interactive protein pairs), the negative dataset is divided into 5 portions and each portion is combined with the positive dataset for one prediction. Thus 5 predictions are performed and the final results are obtained through voting. As a result, the prediction achieves an overall accuracy of 0.8369 with sensitivity of 0.7356. The predictor, developed by this research for the prediction of the fruit fly PPI-nesses, is available for public use at http://chemdata.shu.edu.cn/ppip.
authors.affiliation: Department of Chemistry, College of Sciences, Shanghai University, Shanghai, People's Republic of China.
authors.forename: Liang
authors.initials: L
authors.lastname: Liu
authors.forename: Wen-Cong
authors.initials: WC
authors.lastname: Lu
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
authors.forename: Kai-Yan
authors.initials: KY
authors.lastname: Feng
authors.forename: Chunrong
authors.initials: C
authors.lastname: Peng
authors.forename: Yubei
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D011485:Protein Binding; D060066:Protein Interaction Maps; D011506:Proteins / Q000737:chemistry*
chemical_list: D000596:Amino Acids; D011506:Proteins