Sequence-based prediction of protein-protein interactions by means of rotation forest and autocorrelation descriptor.
We propose a sequence-based multiple classifier system, i.e., rotation forest, to infer protein-protein interactions (PPIs). Moreover, Moran autocorrelation descriptor is used to code an interaction protein pair. Experimental results on Saccharomyces cerevisiae and Helicobacter pylori datasets show that our approach outperforms those previously published in literature, which demonstrates the effectiveness of the proposed method.
Xia
Jun-Feng
JF
Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China.
Han
Kyungsook
K
Huang
De-Shuang
DS
D000465:Algorithms; D001426:Bacterial Proteins / Q000737:chemistry*; D030562:Databases, Protein; D016480:Helicobacter pylori; D010363:Pattern Recognition, Automated / Q000379:methods*; D025941:Protein Interaction Mapping / Q000379:methods*; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry*; D012680:Sensitivity and Specificity; D017421:Sequence Analysis / Q000379:methods*
D001426:Bacterial Proteins; D029701:Saccharomyces cerevisiae Proteins