Authors: Guimarães, Gabriela
Urfer, Wolfgang
Title: Self-Organizing Maps and its Applications in Sleep Apnea Research and Molecular Genetics
Language (ISO): en
Abstract: This paper presents the application of special unsupervised neural networks (self-organizing maps) to different domains, as sleep apnea discovery, protein sequences analysis and tumor classification. An enhancement of the original algorithm, as well as the introduction of several hierachical levels enables the discovery of complex structures as present in this type of applications. Furthermore, an integration of unsupervised neural networks with hidden markov models is proposed.
Subject Headings: Hidden Markov Models
protein sequences
sleep apnea
tumor classification
unsupervised neural networks
URI: http://hdl.handle.net/2003/5028
http://dx.doi.org/10.17877/DE290R-5478
Issue Date: 2000
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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