Composite Gene Module Discovery using Non-negative Independent Component Analysis

Author

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

Author_Institution

Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Arlington, VA

fYear

2006

fDate

38899

Firstpage

1

Lastpage

2

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

Keywords

genetics; independent component analysis; medical computing; molecular biophysics; muscle; biological regulation; composite gene module discovery; functional genomics; gene annotations; muscular dystrophy data; nonnegative independent component analysis; Bioinformatics; Biological processes; Biological system modeling; Cancer; Clustering methods; Cost function; Gene expression; Genomics; Independent component analysis; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Life Science Systems and Applications Workshop, 2006. IEEE/NLM

Conference_Location

Bethesda, MD

Print_ISBN

1-4244-0277-8

Electronic_ISBN

1-4244-0278-6

Type

conf

DOI

10.1109/LSSA.2006.250434

Filename

4015835