DocumentCode
1905680
Title
Finding Characteristic Biology Patterns in Cancer Microarrays
Author
Vass, Keith ; Grindrod, Peter ; Higham, Des ; Kalna, Gabriela ; Spence, Alastair
Author_Institution
Beatson Inst. for Cancer Res., Strathclyde Univ., Glasgow
fYear
2006
fDate
9-9 Nov. 2006
Firstpage
156
Lastpage
166
Abstract
Genetic and environmental differences are known to affect gene expression. The natural variance of expression of many genes affects the control system in any tissue. A finite set of controls must respond to these perturbations, causing regular patterns of altered gene expression characteristic of the system. In order to examine these ideas, a simple method the summarise and test the observed patterns is presented. In this paper, a classified microarray data is used to find relationships between genes. The quantitative data from microarrays can be classified as up or down, allowing estimation of significance by Monte Carlo methods. Spectral analysis and singular value decomposition were also used to study the gene expression pattern. Successive SVD vectors can identify obvious clusters of related genes.
Keywords
Monte Carlo methods; cancer; genetics; medical diagnostic computing; molecular biophysics; singular value decomposition; spectral analysis; Monte Carlo methods; biology patterns; cancer microarrays; gene expression; singular value decomposition; spectral analysis; tissue;
fLanguage
English
Publisher
iet
Conference_Titel
Signal Processing for Genomics, 2006. The Institution of Engineering and Technology Seminar on
Conference_Location
Cambridge
Print_ISBN
0-86341-716-7
Type
conf
Filename
4126038
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