Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme

Research output: Contribution to journalArticlepeer-review

Authors

  • Dong Li
  • Zhisong Pan
  • Guyu Hu
  • Zexuan Zhu
  • Shan He

Colleges, School and Institutes

External organisations

  • PLA University of Science and Technology
  • Shenzhen University, Shenzhen, China.

Abstract

Background: Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. Results: In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. Conclusion: The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Bibliographic note

Funding Information: The authors sincerely thank the editors and reviewers for their patient work. Funding This paper was supported by European Union Seventh Framework Programme (FP7/2007-2013; grant agreement number NMP4-LA-2013-310451) and The Royal Society (BIR002). The publication costs for this article was funded by European Union Seventh Framework Programme (FP7/2007-2013; grant agreement number NMP4-LA-2013-310451). Publisher Copyright: © 2017 The Author(s). Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

Details

Original languageEnglish
Article number209
JournalBMC Genomics
Volume18
Publication statusPublished - 14 Mar 2017

Keywords

  • Connectedness, Memetic algorithm, Module identification, Module size

ASJC Scopus subject areas