Retention prediction using quantitative structure‐retention relationships combined with the hydrophobic subtraction model in reversed‐phase liquid chromatography-Reference-Cited by-同舟云学术

Retention prediction using quantitative structure‐retention relationships combined with the hydrophobic subtraction model in reversed‐phase liquid chromatography

Published:2019-04-29 Issue: Volume: Page:
ISSN:0173-0835
Container-title:ELECTROPHORESIS
language:en
Short-container-title:ELECTROPHORESIS

Author:

Wen Yabin¹,Amos Ruth I. J.¹,Talebi Mohammad¹,Szucs Roman²,Dolan John W.³,Pohl Christopher A.⁴,Haddad Paul R.¹^ORCID

Affiliation:

1. Australian Centre for Research on Separation Science (ACROSS)School of Physical Sciences‐ChemistryUniversity of Tasmania Hobart Australia

2. Pfizer Global Research and Development Sandwich UK

3. LC Resources McMinnville OR USA

4. Thermo Fisher Scientific Sunnyvale CA USA

Funder

Australian Research Council

Publisher

Wiley

Subject

Clinical Biochemistry,Biochemistry,Analytical Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/elps.201900022

Reference22 articles.

1. Comparative characteristics of HPLC columns based on quantitative structure–retention relationships (QSRR) and hydrophobic-subtraction model

2. The Molecular Retention Mechanism in Reversed-Phase Liquid Chromatography of Meso-ionic Compounds by Quantitative Structure-Retention Relationships (QSRR)

3. QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions

4. QSRR Prediction of the Chromatographic Retention Behavior of Painkiller Drugs

5. Retention prediction in reversed phase high performance liquid chromatography using quantitative structure-retention relationships applied to the Hydrophobic Subtraction Model

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