Prediction of Protein-Protein Interactions Using An Effective Sequence Based Combined Method

被引:36
|
作者
Goktepe, Yunus Emre [1 ]
Kodaz, Halife [2 ]
机构
[1] Necmettin Erbakan Univ, Seydisehir Vocat High Sch, Seydisehir, Konya, Turkey
[2] Selcuk Univ, Program Comp Sci, Dept Comp Engn, Fac Engn, Konya, Turkey
关键词
Protein-protein interactions; Sequence-based prediction; Feature extraction; Conjoint triads; Principal component analyses; Support vector machines; AMINO-ACID-COMPOSITION; STRUCTURAL CLASS; FEATURES; DATABASE; FUSION; LOCALIZATION; CONSERVATION; HYPERPLANES; MACHINE;
D O I
10.1016/j.neucom.2018.03.062
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Proteins and their interactions play a key role in the realization of all cellular biological activities of organisms. Therefore, prediction of protein-protein interactions is crucial for elucidating biological processes. Experimental studies are inadequate for some reasons such as the time required to reveal interactions, the fact that it is an expensive way and the number of yet unknown interactions is too great. Thus, a number of computational methods have been developed to predict protein-protein interactions. Generally, many of these methods that produce good results cannot be used without additional biological information such as protein domains, protein structural information, gene neighborhoods, gene expressions, and phylogenetic profiles. Therefore, there is a need for computational methods that can successfully predict interactions using only protein sequences. In this study, we present a novel sequence-based computational model. We applied a new technique called weighted skip-sequential conjoint triads in the proposed method. The results of this research were evaluated on generally used databases and demonstrated its success in this field. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:68 / 74
页数:7
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