Prediction of Protein-Protein Interactions Using An Effective Sequence Based Combined Method
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCIENCE BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Protein-protein interactions, Sequence-based prediction, Feature extraction, Conjoint triads, Principal component analyses, Support vector machines
Kaynak
NEUROCOMPUTING
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
303
