Algorithm of Combining Chromatography–Mass Spectrometry Untargeted Profiling and Multivariate Analysis for Identification of Marker Substances in Samples of Complex Composition-Reference-Cited by-同舟云学术

Algorithm of Combining Chromatography–Mass Spectrometry Untargeted Profiling and Multivariate Analysis for Identification of Marker Substances in Samples of Complex Composition

Published:2021-12 Issue:14 Volume:57 Page:1397-1403
ISSN:0020-1685
Container-title:Inorganic Materials
language:en
Short-container-title:Inorg Mater

Author:

Plyushchenko I. V.,Shakhmatov D. G.,Rodin I. A.

Publisher

Pleiades Publishing Ltd

Subject

Materials Chemistry,Metals and Alloys,Inorganic Chemistry,General Chemical Engineering

Link

https://link.springer.com/content/pdf/10.1134/S0020168521140089.pdf

Reference18 articles.

1. Omics Approaches, Technologies and Applications: Integrative Approaches for Understanding OMICS Data, Arivaradarajan, P. and Misra, G., Eds., Singapore: Springer-Verlag, 2018, 1st ed. https://doi.org/10.1007/978-981-13-2925-8_4

2. Gorrochategui, E., Jaumot, J., Lacorte, S., and Tauler, R., Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: overview and workflow, TrAC, Trends Anal. Chem., 2016, vol. 82, pp. 425–442. https://doi.org/10.1016/j.trac.2016.07.004

3. Argueso, C.T., Assmann, S.M., Birnbaum, K.D., et al., Directions for research and training in plant omics: Big Questions and Big Data, Plant Direct, 2019, vol. 3, no. 4, p. e00133. https://doi.org/10.1002/pld3.133

4. Lozano, D.C.P., Thomas, M.J., Jones, H.E., and Barrow, M.P., Petroleomics: tools, challenges, and developments, Annu. Rev. Anal. Chem., 2020, vol. 13, pp. 405–430. https://doi.org/10.1146/annurev_anchem-091619-091824

5. Ferranti, P., The future of analytical chemistry in foodomics, Curr. Opin. Food Sci., 2018, vol. 22, pp. 102–108. https://doi.org/10.1016/j.cofs.2018.02.005