Sequence-Based Prediction of Protein-Protein Interactions by Means of Rotation Forest and Autocorrelation Descriptor

Title: Sequence-Based Prediction of Protein-Protein Interactions by Means of Rotation Forest and Autocorrelation Descriptor

Volume: 17 Issue: 1

Author(s): Jun-Feng Xia, Kyungsook Han and De-Shuang Huang

Affiliation:

Keywords: Protein-protein interactions, rotation forest, autocorrelation descriptor, protein sequence, multiple classifier system

Abstract: 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.

Cite this article as:

Xia Jun-Feng, Han Kyungsook and Huang De-Shuang, Sequence-Based Prediction of Protein-Protein Interactions by Means of Rotation Forest and Autocorrelation Descriptor, Protein & Peptide Letters 2010; 17 (1) . https://dx.doi.org/10.2174/092986610789909403