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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); You, ZH
2016
发表期刊MOLECULAR BIOSYSTEMS
卷号12期号:12页码:3702-3710
摘要

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
收录类别SCI
WOS记录号WOS:000388946800019
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.xjipc.cas.cn/handle/365002/5123
专题多语种信息技术研究室
通讯作者You, ZH
作者单位1.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
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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 .,...&You, ZH.(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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