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Distribution based nearest neighbor imputation for truncated high dimensional data with applications to pre-clinical and clinical metabolomics studies
BACKGROUND: High throughput metabolomics makes it possible to measure the relative abundances of numerous metabolites in biological samples, which is useful to many areas of biomedical research. However, missing values (MVs) in metabolomics datasets are common and can arise due to both technical and...
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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2017
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5319174/ https://ncbi.nlm.nih.gov/pubmed/28219348 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-017-1547-6 |
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