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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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書誌詳細
出版年:BMC Bioinformatics
主要な著者: Shah, Jasmit S., Rai, Shesh N., DeFilippis, Andrew P., Hill, Bradford G., Bhatnagar, Aruni, Brock, Guy N.
フォーマット: Artigo
言語:Inglês
出版事項: BioMed Central 2017
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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