Composite gene module discovery using non-negative independent component analysis

Ting Gong; Jianhua Xuan; Yitan Zhu; Huai Li; Robert Clarke; Eric P. Hoffman; Yue Wang

doi:10.1109/LSSA.2006.250434

Composite gene module discovery using non-negative independent component analysis

Ting Gong, Jianhua Xuan, Yitan Zhu, Huai Li, Robert Clarke, Eric P. Hoffman, Yue Wang

Epigenetics & Molecular Carcinogenesis

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

1 Scopus citations

Abstract

Gene module discovery can provide comprehensive molecular portrait of biological regulation and functional genomics. We present a new analytic strategy - nonnegative Independent Component Analysis to reveal some gene module composite. The results show that by grouping genes in the latent space, we can find statistically more significant enrichment of gene annotations within clusters. Further, this approach has been applied to a muscular dystrophy data set for gene module discovery.

Original language	English (US)
Title of host publication	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006
DOIs	https://doi.org/10.1109/LSSA.2006.250434
State	Published - 2006
Event	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006 - Bethesda, MD, United States Duration: Jul 13 2006 → Jul 14 2006

Publication series

Name	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

Other

Other	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006
Country/Territory	United States
City	Bethesda, MD
Period	7/13/06 → 7/14/06

ASJC Scopus subject areas

Health(social science)
Assessment and Diagnosis
General Medicine
Health Information Management
Electrical and Electronic Engineering
Human-Computer Interaction
Computer Science Applications
Signal Processing

Access to Document

10.1109/LSSA.2006.250434

Cite this

Gong, T., Xuan, J., Zhu, Y., Li, H., Clarke, R., Hoffman, E. P., & Wang, Y. (2006). Composite gene module discovery using non-negative independent component analysis. In 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006 Article 4015835 (2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006). https://doi.org/10.1109/LSSA.2006.250434

Composite gene module discovery using non-negative independent component analysis. / Gong, Ting; Xuan, Jianhua; Zhu, Yitan et al.
2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006. 2006. 4015835 (2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006).

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

Gong, T, Xuan, J, Zhu, Y, Li, H, Clarke, R, Hoffman, EP & Wang, Y 2006, Composite gene module discovery using non-negative independent component analysis. in 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006., 4015835, 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006, 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006, Bethesda, MD, United States, 7/13/06. https://doi.org/10.1109/LSSA.2006.250434

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abstract = "Gene module discovery can provide comprehensive molecular portrait of biological regulation and functional genomics. We present a new analytic strategy - nonnegative Independent Component Analysis to reveal some gene module composite. The results show that by grouping genes in the latent space, we can find statistically more significant enrichment of gene annotations within clusters. Further, this approach has been applied to a muscular dystrophy data set for gene module discovery.",

author = "Ting Gong and Jianhua Xuan and Yitan Zhu and Huai Li and Robert Clarke and Hoffman, {Eric P.} and Yue Wang",

year = "2006",

doi = "10.1109/LSSA.2006.250434",

language = "English (US)",

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AU - Xuan, Jianhua

AU - Zhu, Yitan

AU - Li, Huai

AU - Clarke, Robert

AU - Hoffman, Eric P.

AU - Wang, Yue

PY - 2006

Y1 - 2006

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AB - Gene module discovery can provide comprehensive molecular portrait of biological regulation and functional genomics. We present a new analytic strategy - nonnegative Independent Component Analysis to reveal some gene module composite. The results show that by grouping genes in the latent space, we can find statistically more significant enrichment of gene annotations within clusters. Further, this approach has been applied to a muscular dystrophy data set for gene module discovery.

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T3 - 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

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T2 - 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

Y2 - 13 July 2006 through 14 July 2006

ER -

Composite gene module discovery using non-negative independent component analysis

Abstract

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Other

ASJC Scopus subject areas

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