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IDA
2005
Springer

Biological Cluster Validity Indices Based on the Gene Ontology

11 years 11 months ago
Biological Cluster Validity Indices Based on the Gene Ontology
With the invention of biotechnological high throughput methods like DNA microarrays and the analysis of the resulting huge amounts of biological data, clustering algorithms gain new popularity. In practice the question arises, which clustering algorithm as well as which parameter set generates the most promising results. Little work is addressed to the question of evaluating and comparing the clustering results, especially according to their biological relevance, as well on distinguishing biologically interesting clusters from less interesting ones. This paper presents two cluster validity indices intended to evaluate clusterings of gene expression data in a biological manner.
Nora Speer, Christian Spieth, Andreas Zell
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IDA
Authors Nora Speer, Christian Spieth, Andreas Zell
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