Toward the General Mechanistic Model of Liquid Chromatographic Retention
Author:
Affiliation:
1. Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Al. Gen. Hallera 107, 80-416 Gdańsk, Poland
Funder
Narodowe Centrum Nauki
European Social Fund
Publisher
American Chemical Society (ACS)
Subject
Analytical Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.2c02034
Reference40 articles.
1. Perspective on the Future Approaches to Predict Retention in Liquid Chromatography
2. Comprehensive and Empirical Evaluation of Machine Learning Algorithms for Small Molecule LC Retention Time Prediction
3. Quantitative Structure Retention Relationship Models in an Analytical Quality by Design Framework: Simultaneously Accounting for Compound Properties, Mobile-Phase Conditions, and Stationary-Phase Properties
4. Performance comparison of partial least squares-related variable selection methods for quantitative structure retention relationships modelling of retention times in reversed-phase liquid chromatography
5. Support Vector Regression Based QSPR for the Prediction of Retention Time of Peptides in Reversed-Phase Liquid Chromatography
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