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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...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2010
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3006395/ https://ncbi.nlm.nih.gov/pubmed/21092268 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-11-571 |
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