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Int. J. Mol. Sci. 2016, 17(1), 21; doi:10.3390/ijms17010021

Detection of Interactions between Proteins through Rotation Forest and Local Phase Quantization Descriptors

1
College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
2
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
3
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editor: Qiang "Shawn" Chen
Received: 10 September 2015 / Revised: 8 December 2015 / Accepted: 9 December 2015 / Published: 24 December 2015
(This article belongs to the Special Issue Protein Engineering)
View Full-Text   |   Download PDF [1183 KB, uploaded 24 December 2015]   |  

Abstract

Protein-Protein Interactions (PPIs) play a vital role in most cellular processes. Although many efforts have been devoted to detecting protein interactions by high-throughput experiments, these methods are obviously expensive and tedious. Targeting these inevitable disadvantages, this study develops a novel computational method to predict PPIs using information on protein sequences, which is highly efficient and accurate. The improvement mainly comes from the use of the Rotation Forest (RF) classifier and the Local Phase Quantization (LPQ) descriptor from the Physicochemical Property Response (PR) Matrix of protein amino acids. When performed on three PPI datasets including Saccharomyces cerevisiae, Homo sapiens, and Helicobacter pylori, we obtained good results of average accuracies of 93.8%, 97.96%, and 89.47%, which are much better than in previous studies. Extensive validations have also been explored to evaluate the performance of the Rotation Forest ensemble classifier with the state-of-the-art Support Vector Machine classifier. These promising results indicate that the proposed method might play a complementary role for future proteomics research. View Full-Text
Keywords: protein-protein interaction; Rotation Forest; Physicochemical Property Response Matrix (PR); Local Phase Quantization protein-protein interaction; Rotation Forest; Physicochemical Property Response Matrix (PR); Local Phase Quantization
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MDPI and ACS Style

Wong, L.; You, Z.-H.; Ming, Z.; Li, J.; Chen, X.; Huang, Y.-A. Detection of Interactions between Proteins through Rotation Forest and Local Phase Quantization Descriptors. Int. J. Mol. Sci. 2016, 17, 21.

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