Multi-objective particle swarm optimization biclustering of microarray data

Junwan Liu; Zhoujun Li; Feifei Liu; Yiming Chen

doi:10.1109/BIBM.2008.17

Multi-objective particle swarm optimization biclustering of microarray data

Junwan Liu^*
, Zhoujun Li
, Feifei Liu
, Yiming Chen

^*Corresponding author for this work

National University of Deference Technology
Central South University of Forestry & Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Scopus citations

Abstract

With the advent of the DNA microarray technology, it is now possible to study the transcriptional response of a complete genome to different experimental conditions. Biclustering is a very useful data mining technique for analysis of those gene expression data. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective modeling is suitable for solving biclustering problem. This paper proposes a novel multi-objective particle swarm optimization biclustering (MOPSOB) algorithm to mine coherent patterns from microarray data. Experimental results on real datasets show that our approach can effectively find significant biclusters of high quality.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008
Pages	363-366
Number of pages	4
DOIs	https://doi.org/10.1109/BIBM.2008.17
State	Published - 2008
Externally published	Yes
Event	2008 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008 - Philadelphia, PA, United States Duration: 3 Nov 2008 → 5 Nov 2008

Publication series

Name	Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008

Conference

Conference	2008 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008
Country/Territory	United States
City	Philadelphia, PA
Period	3/11/08 → 5/11/08

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10.1109/BIBM.2008.17

Cite this

Liu, J., Li, Z., Liu, F., & Chen, Y. (2008). Multi-objective particle swarm optimization biclustering of microarray data. In Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008 (pp. 363-366). Article 4684920 (Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008). https://doi.org/10.1109/BIBM.2008.17

@inproceedings{7eaa96ef60f14f22a8e231b9d2e6a700,

title = "Multi-objective particle swarm optimization biclustering of microarray data",

abstract = "With the advent of the DNA microarray technology, it is now possible to study the transcriptional response of a complete genome to different experimental conditions. Biclustering is a very useful data mining technique for analysis of those gene expression data. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective modeling is suitable for solving biclustering problem. This paper proposes a novel multi-objective particle swarm optimization biclustering (MOPSOB) algorithm to mine coherent patterns from microarray data. Experimental results on real datasets show that our approach can effectively find significant biclusters of high quality.",

author = "Junwan Liu and Zhoujun Li and Feifei Liu and Yiming Chen",

year = "2008",

doi = "10.1109/BIBM.2008.17",

language = "英语",

isbn = "9780769534527",

series = "Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008",

pages = "363--366",

booktitle = "Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008",

note = "2008 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008 ; Conference date: 03-11-2008 Through 05-11-2008",

}

Liu, J, Li, Z, Liu, F & Chen, Y 2008, Multi-objective particle swarm optimization biclustering of microarray data. in Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008., 4684920, Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008, pp. 363-366, 2008 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008, Philadelphia, PA, United States, 3/11/08. https://doi.org/10.1109/BIBM.2008.17

Multi-objective particle swarm optimization biclustering of microarray data. / Liu, Junwan; Li, Zhoujun; Liu, Feifei et al.
Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008. 2008. p. 363-366 4684920 (Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multi-objective particle swarm optimization biclustering of microarray data

AU - Liu, Junwan

AU - Li, Zhoujun

AU - Liu, Feifei

AU - Chen, Yiming

PY - 2008

Y1 - 2008

N2 - With the advent of the DNA microarray technology, it is now possible to study the transcriptional response of a complete genome to different experimental conditions. Biclustering is a very useful data mining technique for analysis of those gene expression data. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective modeling is suitable for solving biclustering problem. This paper proposes a novel multi-objective particle swarm optimization biclustering (MOPSOB) algorithm to mine coherent patterns from microarray data. Experimental results on real datasets show that our approach can effectively find significant biclusters of high quality.

AB - With the advent of the DNA microarray technology, it is now possible to study the transcriptional response of a complete genome to different experimental conditions. Biclustering is a very useful data mining technique for analysis of those gene expression data. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective modeling is suitable for solving biclustering problem. This paper proposes a novel multi-objective particle swarm optimization biclustering (MOPSOB) algorithm to mine coherent patterns from microarray data. Experimental results on real datasets show that our approach can effectively find significant biclusters of high quality.

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DO - 10.1109/BIBM.2008.17

M3 - 会议稿件

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SN - 9780769534527

T3 - Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008

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BT - Proceedings - IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008

T2 - 2008 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2008

Y2 - 3 November 2008 through 5 November 2008

ER -

Multi-objective particle swarm optimization biclustering of microarray data

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