Identifying underlying factors in breast cancer using independent component analysis

Author

Berger, John A. ; Hautaniemi, Sampsa ; Edgren, Henrik ; Monni, Outi ; Mitra, Sanjit ; Yli-Harja, Olli ; Astola, Jaaklco

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

fYear

2003

fDate

17-19 Sept. 2003

Firstpage

81

Lastpage

90

Abstract

Independent component analysis is a well-known tool for extracting underlying mechanisms from an observed set of parallel data. Identifying such components in breast cancer cell lines, for both copy number and gene expression, is proposed here with the goal of identifying mechanisms that affect the evolution of breast cancer in humans. This paper illustrates how to utilize independent component analysis on cell line data for achieving this goal. After the components were estimated for the well-studied chromosome 17, and then over the entire genome for a set of 14 different breast cancer cell lines, ontological analysis was performed in order to determine common gene functions that are present in each of the independent components.

Keywords

cancer; cellular biophysics; genetics; independent component analysis; breast cancer cell lines; gene expression; independent component analysis; ontological analysis; parallel data; underlying factors identification; Bioinformatics; Biological cells; Breast cancer; Cells (biology); Data mining; Gene expression; Genomics; Humans; Independent component analysis; Ontologies;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing, 2003. NNSP'03. 2003 IEEE 13th Workshop on

ISSN

1089-3555

Print_ISBN

0-7803-8177-7

Type

conf

DOI

10.1109/NNSP.2003.1318006

Filename

1318006