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Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data
Principal components analysis (PCA) is a common unsupervised method for the analysis of gene expression microarray data, providing information on the overall structure of the analyzed dataset. In the recent years, it has been applied to very large datasets involving many different tissues and cell t...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4890592/ https://www.ncbi.nlm.nih.gov/pubmed/27254731 http://dx.doi.org/10.1038/srep25696 |