The DOI matches its Crossref record; 215 of the 215 references it cites were found in a registry or an index.
Chemometric methods in data processing of mass spectrometry-based metabolomics: A review
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
KEGG: Kyoto Encyclopedia of Genes and Genomes
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Wu, Y. (1999) · Technometrics · doi:10.1080/00401706.1999.10485951 · Cited by 27,221
Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066
Bootstrap methods: another look at the jackknife
Efron, B. (1979) · The Annals of Statistics · doi:10.1214/aos/1176344552 · Cited by 17,602
A Tutorial on Support Vector Machines for Pattern Recognition
Burges, C. J. C. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009715923555 · Cited by 16,429
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Cross validatory choice and assessment of statistical predictions
Stone, M. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00994.x · Cited by 10,881
PLS-regression: a basic tool of chemometrics
Wold, S., Sjöström, M., & Eriksson, L. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00155-1 · Cited by 10,084
Pattern Recognition and Machine Learning
(2007) · Kybernetes · doi:10.1108/03684920710743466 · Cited by 8,265
Cited by
Recent advances in the application of metabolomics for food safety control and food quality analyses
Li, S., Tian, Y., Jiang, P., Lin, Y., Liu, X., & Yang, H. (2021) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2020.1761287 · Cited by 394
Gorrochategui, E., Jaumot, J., Lacorte, S., & Tauler, R. (2016) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2016.07.004 · Cited by 352
Katchborian-Neto, A., Santos, W. T., Nicácio, K. J., Corrêa, J. O. A., Murgu, M., Martins, T. M. M., Gomes, D. A., Goes, A. M., Soares, M. G., Dias, D. F., et al. (2020) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2020.112743 · Cited by 62
Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials
Abraham, E. J., & Kellogg, J. J. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.780228 · Cited by 64
Metadata
- Authors
- Yi, L., Dong, N., Yun, Y., Deng, B., Ren, D., Liu, S., & Liang, Y.
- Venue
- Analytica Chimica Acta
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 914
- Pages
- 17-34
- ISSN
- 0003-2670 (ISSN-L)
- OpenAlex
- W2280175079
- Cited by
- 305
- References
- 215
- FWCI
- 18.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Chemometric methods in data processing of mass spectrometry-based metabolomics: A review. https://app.cochat.ai/papers/10.1016/j.aca.2016.02.001
- The paper
- Yi, L., Dong, N., Yun, Y., Deng, B., Ren, D., Liu, S., & Liang, Y. (2016). Chemometric methods in data processing of mass spectrometry-based metabolomics: A review. Analytica Chimica Acta. https://doi.org/10.1016/j.aca.2016.02.001
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.
