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

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

doi:10.1186/s12864-017-3495-y

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

Dong Li, Zhisong Pan, Guyu Hu, Zexuan Zhu, Shan He^*

^*Corresponding author for this work

Computer Science

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

48 Downloads (Pure)

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.

Original language	English
Article number	209
Number of pages	9
Journal	BMC Genomics
Volume	18
Issue number	S2
DOIs	https://doi.org/10.1186/s12864-017-3495-y
Publication status	Published - 14 Mar 2017

Bibliographical 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).

Keywords

Connectedness
Memetic algorithm
Module identification
Module size

ASJC Scopus subject areas

Biotechnology
Genetics

Access to Document

10.1186/s12864-017-3495-yLicence: Creative Commons: Attribution (CC BY)

LiD2017ActiveFinal published version, 2.12 MBLicence: Creative Commons: Attribution (CC BY)

Cite this

@article{fc4df7c0fbd74d72a9040b03a10c0877,

title = "Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme",

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.",

keywords = "Connectedness, Memetic algorithm, Module identification, Module size",

author = "Dong Li and Zhisong Pan and Guyu Hu and Zexuan Zhu and Shan He",

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: {\textcopyright} 2017 The Author(s).",

year = "2017",

month = mar,

day = "14",

doi = "10.1186/s12864-017-3495-y",

language = "English",

volume = "18",

journal = "BMC Genomics",

issn = "1471-2164",

publisher = "Springer",

number = "S2",

}

TY - JOUR

T1 - Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme

AU - Li, Dong

AU - Pan, Zhisong

AU - Hu, Guyu

AU - Zhu, Zexuan

AU - He, Shan

N1 - 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).

PY - 2017/3/14

Y1 - 2017/3/14

N2 - 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.

AB - 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.

KW - Connectedness

KW - Memetic algorithm

KW - Module identification

KW - Module size

UR - http://www.scopus.com/inward/record.url?scp=85015190749&partnerID=8YFLogxK

U2 - 10.1186/s12864-017-3495-y

DO - 10.1186/s12864-017-3495-y

M3 - Article

C2 - 28361692

AN - SCOPUS:85015190749

SN - 1471-2164

VL - 18

JO - BMC Genomics

JF - BMC Genomics

IS - S2

M1 - 209

ER -

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this