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
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
收藏
页码:398 / 414
页数:17
相关论文
共 50 条
  • [21] Prediction of protein-protein interactions using symmetrical encoding scheme
    Ni, Qingshan
    Wang, Zhengzhi
    Han, Qingjuan
    Wang, Guangyun
    Zhao, Yingjie
    Li, Gangguo
    2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 740 - +
  • [22] Automated feature engineering improves prediction of protein-protein interactions
    Sumonja, Neven
    Gemovic, Branislava
    Veljkovic, Nevena
    Perovic, Vladimir
    AMINO ACIDS, 2019, 51 (08) : 1187 - 1200
  • [23] Machine-learning techniques for the prediction of protein-protein interactions
    Sarkar, Debasree
    Saha, Sudipto
    JOURNAL OF BIOSCIENCES, 2019, 44 (04)
  • [24] Protein-Protein Interactions and Prediction: A Comprehensive Overview
    Sowmya, Gopichandran
    Ranganathan, Shoba
    PROTEIN AND PEPTIDE LETTERS, 2014, 21 (08) : 779 - 789
  • [25] Computational design of novel protein-protein interactions - An overview on methodological approaches and applications
    Marchand, Anthony
    Van Hall-Beauvais, Alexandra K.
    Correia, Bruno E.
    CURRENT OPINION IN STRUCTURAL BIOLOGY, 2022, 74
  • [26] Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases
    Sarkar, Sharanya
    Gulati, Khushboo
    Kairamkonda, Manikyaprabhu
    Mishra, Amit
    Poluri, Krishna Mohan
    CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2018, 18 (20) : 1719 - 1736
  • [27] Prediction of protein-protein interactions between Ralstonia solanacearum and Arabidopsis thaliana
    Li, Zhi-Gang
    He, Fei
    Zhang, Ziding
    Peng, You-Liang
    AMINO ACIDS, 2012, 42 (06) : 2363 - 2371
  • [28] Recent developments of sequence-based prediction of protein-protein interactions
    Murakami, Yoichi
    Mizuguchi, Kenji
    BIOPHYSICAL REVIEWS, 2022, 14 (06) : 1393 - 1411
  • [29] Prediction-based fingerprints of protein-protein interactions
    Porollo, Aleksey
    Meller, Jaroslaw
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2007, 66 (03) : 630 - 645
  • [30] Protein Features Identification for Machine Learning-Based Prediction of Protein-Protein Interactions
    Raza, Khalid
    INFORMATION, COMMUNICATION AND COMPUTING TECHNOLOGY, 2017, 750 : 305 - 317