Literature DB >> 32065215

idenPC-MIIP: identify protein complexes from weighted PPI networks using mutual important interacting partner relation.

Zhourun Wu1, Qing Liao1, Bin Liu2.   

Abstract

Protein complexes are key units for studying a cell system. During the past decades, the genome-scale protein-protein interaction (PPI) data have been determined by high-throughput approaches, which enables the identification of protein complexes from PPI networks. However, the high-throughput approaches often produce considerable fraction of false positive and negative samples. In this study, we propose the mutual important interacting partner relation to reflect the co-complex relationship of two proteins based on their interaction neighborhoods. In addition, a new algorithm called idenPC-MIIP is developed to identify protein complexes from weighted PPI networks. The experimental results on two widely used datasets show that idenPC-MIIP outperforms 17 state-of-the-art methods, especially for identification of small protein complexes with only two or three proteins.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  mutual important interacting partner relation; protein complexes; protein–protein interaction networks

Year:  2021        PMID: 32065215     DOI: 10.1093/bib/bbaa016

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  4 in total

Review 1.  Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward.

Authors:  Sara Omranian; Zoran Nikoloski; Dominik G Grimm
Journal:  Comput Struct Biotechnol J       Date:  2022-05-27       Impact factor: 6.155

2.  Constraint-based models for dominating protein interaction networks.

Authors:  Adel A Alofairi; Emad Mabrouk; Ibrahim E Elsemman
Journal:  IET Syst Biol       Date:  2021-05-28       Impact factor: 1.615

3.  A New Method for Recognizing Protein Complexes Based on Protein Interaction Networks and GO Terms.

Authors:  Xiaoting Wang; Nan Zhang; Yulan Zhao; Juan Wang
Journal:  Front Genet       Date:  2021-12-13       Impact factor: 4.599

4.  Detecting protein complexes with multiple properties by an adaptive harmony search algorithm.

Authors:  Rongquan Wang; Caixia Wang; Huimin Ma
Journal:  BMC Bioinformatics       Date:  2022-10-07       Impact factor: 3.307

  4 in total

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