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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2014
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| 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 |