Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models-Reference-Cited by-同舟云学术

Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models

Published:2005-02-22 Issue:2 Volume:4 Page:555-563
ISSN:1535-3893
Container-title:Journal of Proteome Research
language:en
Short-container-title:J. Proteome Res.

Author:

Ba̧czek Tomasz¹,Wiczling Paweł¹,Marszałł Michał¹,Heyden Yvan Vander¹,Kaliszan Roman¹

Affiliation:

1. Medical University of Gdańsk, Department of Biopharmaceutics and Pharmacodynamics, Gdańsk, Poland and Vrije Universiteit Brussel−VUB, Department of Analytical Chemistry and Pharmaceutical Technology, Brussels, Belgium.

Publisher

American Chemical Society (ACS)

Subject

General Chemistry,Biochemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/pr049780r

Reference27 articles.

1. Prediction of gradient retention from the linear solvent strength (LSS) model, quantitative structure-retention relationships (QSRR), and artificial neural networks (ANN)

2. Combination of linear solvent strength model and quantitative structure–retention relationships as a comprehensive procedure of approximate prediction of retention in gradient liquid chromatography

3. Predictive approaches to gradient retention based on analyte structural descriptors from calculation chemistry

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