Computational Approaches for the Prediction of Protein-Protein Interactions: A Survey

被引：0

作者：

Theofilatos, Konstantinos A. ^{[1
]}

Dimitrakopoulos, Christos M. ^{[1
]}

Tsakalidis, Athanasios K. ^{[1
]}

Likothanassis, Spyridon D. ^{[1
]}

Papadimitriou, Stergios T. ^{[2
]}

Mavroudi, Seferina P. ^{[1
]}

机构：

[1] Univ Patras, Dept Comp Engn & Informat, GR-26500 Patras, Greece

[2] Technol Inst Kavala, Dept Informat Management, GR-65404 Kavala, Greece

来源：

CURRENT BIOINFORMATICS | 2011年 / 6卷 / 04期

关键词：

Protein-Protein interactions; computational methods; machine learning; databases; experimental methods; SVM; random forests; Bayesian Classifiers; Neural Networks; SUPPORT VECTOR MACHINE; SUBCELLULAR-LOCALIZATION; INTERACTION NETWORKS; INTERACTION DATABASE; MOLECULAR DOCKING; GENE-EXPRESSION; SEQUENCE; INTERFACES; GENOMES; IDENTIFICATION;

D O I：

暂无

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Protein-Protein Interactions (PPIs) play a very important role in many cellular processes and a variety of experimental approaches have been developed for their identification. These approaches however are partial, time-consuming and they usually suffer from high error rates. Recently, computational methods have been employed to assist for the prediction producing encouraging results. With this work we offer a critical review of recent computational PPI prediction methods by evaluating their strengths and limitations. Moreover we discuss open problems common to all schemes and try to suggest solutions. Finally we propose future research directions which could potentially more effectively handle some of the restrictions of existing approaches.

引用

页码：398 / 414

页数：17

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