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Probabilistic principal component analysis for metabolomic data
BACKGROUND: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. RESULTS: H...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3006395/ https://www.ncbi.nlm.nih.gov/pubmed/21092268 http://dx.doi.org/10.1186/1471-2105-11-571 |