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Bayesian Hierarchical Clustering for Studying Cancer Gene Expression Data with Unknown Statistics
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm....
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2013
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3806770/ https://www.ncbi.nlm.nih.gov/pubmed/24194826 http://dx.doi.org/10.1371/journal.pone.0075748 |