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Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information
An, JY (An, Ji-Yong); You, ZH (You, Zhu-Hong); Chen, X (Chen, Xing); Huang, DS (Huang, De-Shuang); Yan, GY (Yan, Guiying); Wang, DF (Wang, Da-Fu)
2016
Source PublicationMOLECULAR BIOSYSTEMS
ISSN1742-206X
Volume12Issue:12Pages:3702-3710
Abstract

Self-interacting proteins (SIPs) play an essential role in cellular functions and the evolution of protein interaction networks (PINs). Due to the limitations of experimental self-interaction proteins detection technology, it is a very important task to develop a robust and accurate computational approach for SIPs prediction. In this study, we propose a novel computational method for predicting SIPs from protein amino acids sequence. Firstly, a novel feature representation scheme based on Local Binary Pattern (LBP) is developed, in which the evolutionary information, in the form of multiple sequence alignments, is taken into account. Then, by employing the Relevance Vector Machine (RVM) classifier, the performance of our proposed method is evaluated on yeast and human datasets using a five-fold cross-validation test. The experimental results show that the proposed method can achieve high accuracies of 94.82% and 97.28% on yeast and human datasets, respectively. For further assessing the performance of our method, we compared it with the state-of-the-art Support Vector Machine (SVM) classifier, and other existing methods, on the same datasets. Comparison results demonstrate that the proposed method is very promising and could provide a cost-effective alternative for predicting SIPs. In addition, to facilitate extensive studies for future proteomics research, a web server is freely available for academic use at http://219.219.62.123:8888/HASIPP.

DOI10.1039/c6mb00599c
Indexed BySCI
WOS IDWOS:000388946800019
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/5123
Collection多语种信息技术研究室
Corresponding AuthorYou, ZH (You, Zhu-Hong)
Affiliation1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 21116, Peoples R China
2.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China
3.China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Jiangsu, Peoples R China
4.Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China
5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
An, JY ,You, ZH ,Chen, X ,et al. Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information[J]. MOLECULAR BIOSYSTEMS,2016,12(12):3702-3710.
APA An, JY ,You, ZH ,Chen, X ,Huang, DS ,Yan, GY ,&Wang, DF .(2016).Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information.MOLECULAR BIOSYSTEMS,12(12),3702-3710.
MLA An, JY ,et al."Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information".MOLECULAR BIOSYSTEMS 12.12(2016):3702-3710.
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