MIClique : An Algorithm to Identify Differentially Coexpressed Disease Gene Subset from Microarray Data
Joint Authors
Zhang, Huanping
Wang, Huinan
Zhang, Xiaobai
Song, Xiaofeng
Source
Journal of Biomedicine and Biotechnology
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-01-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Computational analysis of microarray data has provided an effective way to identify disease-related genes.
Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization.
These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes.
In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis.
Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples.
Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function.
By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset.
American Psychological Association (APA)
Zhang, Huanping& Song, Xiaofeng& Wang, Huinan& Zhang, Xiaobai. 2010. MIClique : An Algorithm to Identify Differentially Coexpressed Disease Gene Subset from Microarray Data. Journal of Biomedicine and Biotechnology،Vol. 2009, no. 2009, pp.1-9.
https://search.emarefa.net/detail/BIM-487605
Modern Language Association (MLA)
Zhang, Huanping…[et al.]. MIClique : An Algorithm to Identify Differentially Coexpressed Disease Gene Subset from Microarray Data. Journal of Biomedicine and Biotechnology No. 2009 (2009), pp.1-9.
https://search.emarefa.net/detail/BIM-487605
American Medical Association (AMA)
Zhang, Huanping& Song, Xiaofeng& Wang, Huinan& Zhang, Xiaobai. MIClique : An Algorithm to Identify Differentially Coexpressed Disease Gene Subset from Microarray Data. Journal of Biomedicine and Biotechnology. 2010. Vol. 2009, no. 2009, pp.1-9.
https://search.emarefa.net/detail/BIM-487605
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-487605