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Highly Efficient Framework for Predicting Interactions Between Proteins
You, ZH (You, Zhu-Hong); Zhou, MC (Zhou, MengChu); Luo, X (Luo, Xin); Li, S (Li, Shuai)
2017
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
Volume47Issue:3Pages:731-743
Abstract

Protein-protein interactions (PPIs) play a central role in many biological processes. Although a large amount of human PPI data has been generated by high-throughput experimental techniques, they are very limited compared to the estimated 130 000 protein interactions in humans. Hence, automatic methods for human PPI-detection are highly desired. This work proposes a novel framework, i. e., Low-rank approximationkernel Extreme Learning Machine (LELM), for detecting human PPI from a protein's primary sequences automatically. It has three main steps: 1) mapping each protein sequence into a matrix built on all kinds of adjacent amino acids; 2) applying the low-rank approximation model to the obtained matrix to solve its lowest rank representation, which reflects its true subspace structures; and 3) utilizing a powerful kernel extreme learning machine to predict the probability for PPI based on this lowest rank representation. Experimental results on a large-scale human PPI dataset demonstrate that the proposed LELM has significant advantages in accuracy and efficiency over the state-of-art approaches. Hence, this work establishes a new and effective way for the automatic detection of PPI.

KeywordBig Data Feature Extraction Kernel Extreme Learning Machine (K-elm) Low-rank Approximation (Lra) Protein-protein Interactions (Ppis) Support Vector Machine (Svm)
DOI10.1109/TCYB.2016.2524994
Indexed BySCI
WOS IDWOS:000396395400016
Citation statistics
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/4743
Collection多语种信息技术研究室
Affiliation1.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China
2.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
3.New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
4.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
5.Hong Kong Polytech Univ, Dept Comp, Hong Kong 999077, Hong Kong, Peoples R China
Recommended Citation
GB/T 7714
You, ZH ,Zhou, MC ,Luo, X ,et al. Highly Efficient Framework for Predicting Interactions Between Proteins[J]. IEEE TRANSACTIONS ON CYBERNETICS,2017,47(3):731-743.
APA You, ZH ,Zhou, MC ,Luo, X ,&Li, S .(2017).Highly Efficient Framework for Predicting Interactions Between Proteins.IEEE TRANSACTIONS ON CYBERNETICS,47(3),731-743.
MLA You, ZH ,et al."Highly Efficient Framework for Predicting Interactions Between Proteins".IEEE TRANSACTIONS ON CYBERNETICS 47.3(2017):731-743.
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