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Influence of Missing Values Substitutes on Multivariate Analysis of Metabolomics Data
Missing values are known to be problematic for the analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data. Typically these values cover about 10%–20% of all data and can originate from various backgrounds, including analytical, computational, as well as biological. Currently, the...
Autores principales: | Gromski, Piotr S., Xu, Yun, Kotze, Helen L., Correa, Elon, Ellis, David I., Armitage, Emily Grace, Turner, Michael L., Goodacre, Royston |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101515/ https://www.ncbi.nlm.nih.gov/pubmed/24957035 http://dx.doi.org/10.3390/metabo4020433 |
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