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....

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Detalles Bibliográficos
Autores principales: Sirinukunwattana, Korsuk, Savage, Richard S., Bari, Muhammad F., Snead, David R. J., Rajpoot, Nasir M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
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

Internet

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

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