Editorial: special issue machine learning and other tools for data handling in chromatography
Author:
Publisher
Elsevier BV
Subject
Organic Chemistry,General Medicine,Biochemistry,Analytical Chemistry
Reference10 articles.
1. Building machine-learning-based models for retention time and resolution predictions in ion pair chromatography of oligonucleotides;Enmark;J. Chromatogr. A,2022
2. Transfer of gas chromatographic retention data among poly(siloxane) columns by quantitative structure-retention relationships based on molecular descriptors of both solutes and stationary phases;Biancolillo;J. Chromatogr. A,2022
3. Yvan Vander Heyden, Evaluating micellar liquid chromatographic methods on octadecyl particle-based and monolithic columns to predict the skin permeation of drug and cosmetic molecules;Grooten;J. Chromatogr. A,2022
4. Non-targeted gas chromatography orbitrap mass spectrometry qualitative and quantitative analysis of semi-volatile organic compounds in indoor dust using the regions of interest multivariate curve resolution chemometrics procedure;Pourasil;J. Chromatogr. A,2022
5. Secondary-metabolites fingerprinting of Argania spinosa kernels using liquid chromatography–mass spectrometry and chemometrics, for metabolite identification and quantification as well as for geographic classification;Kharbach;J. Chromatogr. A,2022
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