A new information-theoretic approach to detect gene-gene interactions in case-control studies

Xiangdong Zhou; Chun Chung Chan

doi:10.1109/BIBE.2015.7367739

A new information-theoretic approach to detect gene-gene interactions in case-control studies

Xiangdong Zhou, Chun Chung Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

Gene-gene interaction is an important factor to consider in selecting genes in genotype data or microarray expression data for association with diseases. However current definitions of gene-gene interaction are not very clear and accurate. An inequality is proved in this paper and a new definition of gene-gene interaction: conditional independence and redundancy based definition of gene-gene interaction (CIR), together with a definition of interaction group are proposed according to this inequality. A new algorithm to detect gene-gene interaction with order greater than two is also proposed based on these new definitions and a theorem. Experimental results show the usefulness of these new definitions and the effectiveness and efficiency of this new algorithm.

Original language	English
Title of host publication	2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
Publisher	IEEE
ISBN (Electronic)	9781467379830
DOIs	https://doi.org/10.1109/BIBE.2015.7367739
Publication status	Published - 28 Dec 2015
Event	15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015 - Belgrade, Serbia Duration: 2 Nov 2015 → 4 Nov 2015

Conference

Conference	15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015
Country/Territory	Serbia
City	Belgrade
Period	2/11/15 → 4/11/15

ASJC Scopus subject areas

Biotechnology
Computer Science Applications
Biomedical Engineering
Health Informatics

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10.1109/BIBE.2015.7367739

Cite this

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abstract = "Gene-gene interaction is an important factor to consider in selecting genes in genotype data or microarray expression data for association with diseases. However current definitions of gene-gene interaction are not very clear and accurate. An inequality is proved in this paper and a new definition of gene-gene interaction: conditional independence and redundancy based definition of gene-gene interaction (CIR), together with a definition of interaction group are proposed according to this inequality. A new algorithm to detect gene-gene interaction with order greater than two is also proposed based on these new definitions and a theorem. Experimental results show the usefulness of these new definitions and the effectiveness and efficiency of this new algorithm.",

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Zhou, X & Chan, CC 2015, A new information-theoretic approach to detect gene-gene interactions in case-control studies. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015., 7367739, IEEE, 15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015, Belgrade, Serbia, 2/11/15. https://doi.org/10.1109/BIBE.2015.7367739

A new information-theoretic approach to detect gene-gene interactions in case-control studies. / Zhou, Xiangdong; Chan, Chun Chung.
2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. IEEE, 2015. 7367739.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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N2 - Gene-gene interaction is an important factor to consider in selecting genes in genotype data or microarray expression data for association with diseases. However current definitions of gene-gene interaction are not very clear and accurate. An inequality is proved in this paper and a new definition of gene-gene interaction: conditional independence and redundancy based definition of gene-gene interaction (CIR), together with a definition of interaction group are proposed according to this inequality. A new algorithm to detect gene-gene interaction with order greater than two is also proposed based on these new definitions and a theorem. Experimental results show the usefulness of these new definitions and the effectiveness and efficiency of this new algorithm.

AB - Gene-gene interaction is an important factor to consider in selecting genes in genotype data or microarray expression data for association with diseases. However current definitions of gene-gene interaction are not very clear and accurate. An inequality is proved in this paper and a new definition of gene-gene interaction: conditional independence and redundancy based definition of gene-gene interaction (CIR), together with a definition of interaction group are proposed according to this inequality. A new algorithm to detect gene-gene interaction with order greater than two is also proposed based on these new definitions and a theorem. Experimental results show the usefulness of these new definitions and the effectiveness and efficiency of this new algorithm.

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A new information-theoretic approach to detect gene-gene interactions in case-control studies

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