Analyzing microarray data with the Generative Topographic Mapping approach

被引：0
|
作者：
Grimmenstein, IM [1 ]
Quast, K
Urfer, W
机构：
[1] Univ Dortmund, Fachbereich Stat, D-44221 Dortmund, Germany
[2] Boehringer Ingelheim Pharm GmbH & Co KG, D-88397 Biberach Riss, Germany
来源：
Classification - the Ubiquitous Challenge | 2005年
关键词：
D O I：
10.1007/3-540-28084-7_38
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The Generative Topographic Mapping (GTM) approach of Bishop et al. (1998) is proposed as an alternative to the Self-Organizing Map (SOM) approach of Kohonen (1998) for the analysis of gene expression data from microarrays. It is applied exemplarily to a microarray data set from renal tissue and the results are compared with those derived by SOM. Furthermore, enhancements for the application of the GTM methodology to microarray data are made.
引用
收藏
页码：338 / 345
页数：8
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