Clustering Analysis of Micro-array Data Based on the SOM Algorithm

Author

Xiuming Zou ; Huaijiang Sun

Author_Institution

Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China

fYear

2013

fDate

14-15 Dec. 2013

Firstpage

308

Lastpage

312

Abstract

In this paper, characteristics of gene micro-array data are combined, the clustering analysis principle of the self-organizing map (SOM) is discussed, and experiments are conducted on the basis of public gene expression data sets. The experimental results show that the SOM network has higher classification accuracy and is available for the clustering analysis of gene expression data.

Keywords

bioinformatics; pattern clustering; self-organising feature maps; SOM algorithm; clustering analysis; gene micro-array data; public gene expression data sets; self-organizing map; Algorithm design and analysis; Arrays; Clustering algorithms; Educational institutions; Gene expression; Neurons; Training; cluster; micro-array; self organizing map;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2013 9th International Conference on

Conference_Location

Leshan

Print_ISBN

978-1-4799-2548-3

Type

conf

DOI

10.1109/CIS.2013.72

Filename

6746408

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3367949