Analyzing protein data with the generative topographic mapping approach

被引：0
|
作者：
Grimmenstein, IM [1 ]
Urfer, W [1 ]
机构：
[1] Univ Dortmund, Fachbereich Stat, D-44221 Dortmund, Germany
来源：
INNOVATIONS IN CLASSIFICATION, DATA SCIENCE, AND INFORMATION SYSTEMS | 2005年
关键词：
D O I：
10.1007/3-540-26981-9_67
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Generative Topographic Mapping (GTM) approach by Bishop et al. (1998) is used for the classification of sequences from a protein family and the graphical display of the group relationships on a two-dimensional map. The results are compared with the closely related Self-Organizing Map (SOM) approach of Kohonen (1982). A modification of the classical GTM approach is presented, better suited for the analysis of sequence data.
引用
收藏
页码：585 / 592
页数：8
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