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Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics
Analysis of differential abundance in proteomics data sets requires careful application of missing value imputation. Missing abundance values widely vary when performing comparisons across different sample treatments. For example, one would expect a consistent rate of “missing at random” (MAR) acros...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431783/ https://www.ncbi.nlm.nih.gov/pubmed/34502557 http://dx.doi.org/10.3390/ijms22179650 |