On the selection of appropriate distances for gene expression data clustering

BACKGROUND: Clustering is crucial for gene expression data analysis. As an unsupervised exploratory procedure its results can help researchers to gain insights and formulate new hypothesis about biological data from microarrays. Given different settings of microarray experiments, clustering proves i...

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Detalles Bibliográficos
Autores principales: Jaskowiak, Pablo A, Campello, Ricardo JGB, Costa, Ivan G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072854/
https://www.ncbi.nlm.nih.gov/pubmed/24564555
http://dx.doi.org/10.1186/1471-2105-15-S2-S2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072854/
https://www.ncbi.nlm.nih.gov/pubmed/24564555
http://dx.doi.org/10.1186/1471-2105-15-S2-S2

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