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A Pohl

Showing results (181-190 of 231) with videos related to

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Wiener Klinische Wochenschrift|November 21, 1980
[Developments in the serological diagnosis of malignant diseases]K Moser, F Dorner, M Francesconi, et al.
Analytical Chemistry|February 18, 2017
Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of ExperimentsMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|January 5, 2017
Prediction of retention in hydrophilic interaction liquid chromatography using solute molecular descriptors based on chemical structuresMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|July 31, 2012
Determination of pharmaceutically related compounds by suppressed ion chromatography: IV. Interfacing ion chromatography with universal detectorsNaama Karu, Joseph P Hutchinson, Greg W Dicinoski, et al.
Journal of Chemical Information and Modeling|October 14, 2017
Benchmarking of Computational Methods for Creation of Retention Models in Quantitative Structure-Retention Relationships StudiesRuth I J Amos, Eva Tyteca, Mohammad Talebi, et al.
Nature Communications|July 8, 2016
High potential for weathering and climate effects of non-vascular vegetation in the Late OrdovicianP Porada, T M Lenton, A Pohl, et al.
Journal of Chromatography. A|October 18, 2017
Error measures in quantitative structure-retention relationships studiesMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|June 8, 2017
Use of dual-filtering to create training sets leading to improved accuracy in quantitative structure-retention relationships modelling for hydrophilic interaction liquid chromatographic systemsMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Analytical Chemistry|June 29, 2018
Retention Index Prediction Using Quantitative Structure-Retention Relationships for Improving Structure Identification in Nontargeted MetabolomicsYabin Wen, Ruth I J Amos, Mohammad Talebi, et al.
Journal of Chromatography. A|February 19, 2018
Retention prediction in reversed phase high performance liquid chromatography using quantitative structure-retention relationships applied to the Hydrophobic Subtraction ModelYabin Wen, Mohammad Talebi, Ruth I J Amos, et al.
Pageof 24

Showing results (181-190 of 231) with videos related to

Sort By:
Pageof 24
Wiener Klinische Wochenschrift|November 21, 1980
[Developments in the serological diagnosis of malignant diseases]K Moser, F Dorner, M Francesconi, et al.
Analytical Chemistry|February 18, 2017
Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of ExperimentsMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|January 5, 2017
Prediction of retention in hydrophilic interaction liquid chromatography using solute molecular descriptors based on chemical structuresMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|July 31, 2012
Determination of pharmaceutically related compounds by suppressed ion chromatography: IV. Interfacing ion chromatography with universal detectorsNaama Karu, Joseph P Hutchinson, Greg W Dicinoski, et al.
Journal of Chemical Information and Modeling|October 14, 2017
Benchmarking of Computational Methods for Creation of Retention Models in Quantitative Structure-Retention Relationships StudiesRuth I J Amos, Eva Tyteca, Mohammad Talebi, et al.
Nature Communications|July 8, 2016
High potential for weathering and climate effects of non-vascular vegetation in the Late OrdovicianP Porada, T M Lenton, A Pohl, et al.
Journal of Chromatography. A|October 18, 2017
Error measures in quantitative structure-retention relationships studiesMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Journal of Chromatography. A|June 8, 2017
Use of dual-filtering to create training sets leading to improved accuracy in quantitative structure-retention relationships modelling for hydrophilic interaction liquid chromatographic systemsMaryam Taraji, Paul R Haddad, Ruth I J Amos, et al.
Analytical Chemistry|June 29, 2018
Retention Index Prediction Using Quantitative Structure-Retention Relationships for Improving Structure Identification in Nontargeted MetabolomicsYabin Wen, Ruth I J Amos, Mohammad Talebi, et al.
Journal of Chromatography. A|February 19, 2018
Retention prediction in reversed phase high performance liquid chromatography using quantitative structure-retention relationships applied to the Hydrophobic Subtraction ModelYabin Wen, Mohammad Talebi, Ruth I J Amos, et al.
Pageof 24