The Sensitivity of Spectral Clustering Applied to Gene Expression Data

Author

Spence, Alastair ; Stoyanov, Zhivko ; Vass, J. Keith

Author_Institution

Dept. of Math. Sci., Bath Univ., Bath

fYear

2007

fDate

6-8 July 2007

Firstpage

1343

Lastpage

1346

Abstract

In large scale numerical datasets which are to be ordered or clustered it is important to be able to measure the sensitivity of the orderings or clusterings. In this paper we combine statistical methods with techniques from numerical linear algebra to obtain an efficient numerical method to measure the sensitivity of spectral clustering. The method is applied to answer a question about the expression of genes MYH11 and NDE1 in breast cancer samples.

Keywords

biology computing; cancer; genetics; singular value decomposition; statistics; breast cancer; gene MYH11; gene NDE1; gene expression data; numerical linear algebra; spectral clustering; statistical methods; Breast cancer; Computational efficiency; Gene expression; Large-scale systems; Linear algebra; Matrix decomposition; Sensitivity analysis; Singular value decomposition; Statistical analysis; Thumb;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on

Conference_Location

Wuhan

Print_ISBN

1-4244-1120-3

Type

conf

DOI

10.1109/ICBBE.2007.347

Filename

4272831

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3052977