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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...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4072854/ https://ncbi.nlm.nih.gov/pubmed/24564555 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-15-S2-S2 |
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