Abstract
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.
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Grimmenstein, I.M., Quast, K., Urfer, W. (2005). Analyzing Microarray Data with the Generative Topographic Mapping Approach. In: Weihs, C., Gaul, W. (eds) Classification — the Ubiquitous Challenge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28084-7_38
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DOI: https://doi.org/10.1007/3-540-28084-7_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25677-9
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