Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-017-19120-0.pdf
Reference34 articles.
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2. Bijlsma, S. et al. Large-scale human metabolomics studies: A strategy for data (pre-) processing and validation. Analytical Chemistry 78, 567–574, https://doi.org/10.1021/ac051495j (2006).
3. Hrydziuszko, O. & Viant, M. R. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline. Metabolomics 8, 161–174, https://doi.org/10.1007/s11306-011-0366-4 (2012).
4. Gelman, A. & Hill, J. Data analysis using regression and multilevel/hierarchical models. 529–542 (Cambridge University Press, 2006).
5. Little, R. J. A. & Rubin, D. B. Statistical Analysis with Missing Data. 11-19 (John Wiley & Sons, 2002).
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