Application of singular value decomposition and functional clustering to analyzing gene expression profiles of renal cell carcinoma

Author

Duan, Zhong-Hui ; Liou, Louis S. ; Shi, Ting ; DiDonato, Joseph A.

Author_Institution

Dept. of Comput. Sci., Akron Univ., OH, USA

fYear

2003

fDate

11-14 Aug. 2003

Firstpage

392

Lastpage

393

Abstract

Microarray gene expression profiles of both renal cell carcinoma (RCC) tissues and a RCC cell line were analyzed using singular value decomposition (SVD) and functional clustering. The SVD projections of the expression profiles revealed significant differences between the profiles of RCC tissues and a RCC cell line. Based on the biological processes, selected genes were annotated and clustered into functional groups. The analysis of each functional group revealed remarkable gene expression alterations in the biological pathways in RCC and provided insights into understanding the molecular mechanism of renal cell carcinogenesis.

Keywords

arrays; biological tissues; cellular biophysics; genetics; kidney; singular value decomposition; biological pathways; cell line; functional clustering; gene annotation; gene expression; microarray gene expression; molecular mechanism; renal cell carcinogenesis; renal cell carcinoma; singular value decomposition; tissues; Application software; Biological processes; Cells (biology); Computer science; Data visualization; Gene expression; Matrix decomposition; Ontologies; RNA; Singular value decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE

Print_ISBN

0-7695-2000-6

Type

conf

DOI

10.1109/CSB.2003.1227341

Filename

1227341