The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline
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Cites
mice: Multivariate Imputation by Chained Equations in R
Buuren, S. V., & Groothuis-Oudshoorn, K. (2011) · Journal of Statistical Software · doi:10.18637/jss.v045.i03 · Cited by 13,870
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
A test of missing completely at random for multivariate data with missing values
Little, R. J. A. (1988) · Journal of the American Statistical Association · doi:10.1080/01621459.1988.10478722 · Cited by 8,963
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., Fan, T. W.-M., Fiehn, O., Goodacre, R., Griffin, J. L., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0082-2 · Cited by 5,368
Self-citationSchafer, J. L. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800102 · Cited by 3,949
Assessment of PLSDA Cross Validation
Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., van Duijnhoven, J. P. M., & van Dorsten, F. A. (2008) · Metabolomics · doi:10.1007/s11306-007-0099-6 · Cited by 1,471
Cited by
Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
Wei, R., Wang, J., Su, M., Jia, E., Chen, S., Chen, T., & Ni, Y. (2018) · Scientific Reports · doi:10.1038/s41598-017-19120-0 · Cited by 707
Reflections on univariate and multivariate analysis of metabolomics data
Saccenti, E., Hoefsloot, H. C. J., Smilde, A. K., Westerhuis, J. A., & Hendriks, M. M. W. B. (2014) · Metabolomics · doi:10.1007/s11306-013-0598-6 · Cited by 658
Di Guida, R., Engel, J., Allwood, J. W., Weber, R. J. M., Jones, M. R., Sommer, U., Viant, M. R., & Dunn, W. B. (2016) · Metabolomics · doi:10.1007/s11306-016-1030-9 · Cited by 371
Self-citationMachine Learning Applications for Mass Spectrometry-Based Metabolomics
Liebal, U. W., Phan, A. N. T., Sudhakar, M., Raman, K., & Blank, L. M. (2020) · Metabolites · doi:10.3390/metabo10060243 · Cited by 357
Kuehnbaum, N. L., & Britz-McKibbin, P. (2013) · Chemical Reviews · doi:10.1021/cr300484s · Cited by 354
Metadata
- Authors
- Hrydziuszko, O., & Viant, M. R.
- Venue
- Metabolomics
- Published
- 2011-10-08
- Volume
- 8
- Issue
- S1
- Pages
- 161-174
- ISSN
- 1573-3882 (ISSN-L)
- 1573-3890
- OpenAlex
- W2099598705
- Cited by
- 224
- References
- 7
- FWCI
- 4.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline. https://app.cochat.ai/papers/10.1007/s11306-011-0366-4
- The paper
- Hrydziuszko, O., & Viant, M. R. (2012). Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline. Metabolomics. https://doi.org/10.1007/s11306-011-0366-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
