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A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis
Highlights: Developed a data preprocessing strategy to cope with missing values and mask effects in data analysis from high variation of abundant metabolites. A new method- ‘x-VAST’ was developed to amend the measurement deviation enlargement. Applying the above strategy, several low abundant masked...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2015
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4428451/ https://www.ncbi.nlm.nih.gov/pubmed/25988172 http://dx.doi.org/10.3389/fmolb.2015.00004 |