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Journal of Medicinal Chemistry
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January 22, 1998
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations
S S So, M Karplus
Journal of Computer-Aided Molecular Design
|
April 27, 1999
A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors
S S So, M Karplus
Journal of Medicinal Chemistry
|
December 20, 1996
Genetic neural networks for quantitative structure-activity relationships: improvements and application of benzodiazepine affinity for benzodiazepine/GABAA receptors
S S So, M Karplus
Journal of Medicinal Chemistry
|
January 22, 1998
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 2. Applications
S S So, M Karplus
Journal of Computer-Aided Molecular Design
|
November 2, 2001
Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches
S S So, M Karplus
Journal of Chemical Information and Computer Sciences
|
December 26, 2001
Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery. 1. Aqueous solubility
R Liu, S S So
Journal of Medicinal Chemistry
|
March 29, 1996
Evolutionary optimization in quantitative structure-activity relationship: an application of genetic neural networks
S S So, M Karplus
Journal of Medicinal Chemistry
|
August 21, 1992
Application of neural networks: quantitative structure-activity relationships of the derivatives of 2,4-diamino-5-(substituted-benzyl)pyrimidines as DHFR inhibitors
S S So, W G Richards
Journal of Chemical Information and Computer Sciences
|
December 26, 2001
Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery. 2. Blood-brain barrier penetration
R Liu, H Sun, S S So
Proteins
|
October 21, 1998
Use of quantitative structure-property relationships to predict the folding ability of model proteins
A R Dinner, S S So, M Karplus
Page
of 3
Search research articles
Search
Showing results (1-10 of 24) with videos related to
Sort By:
Page
of 3
Journal of Medicinal Chemistry
|
January 22, 1998
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 1. Method and validations
S S So, M Karplus
Journal of Computer-Aided Molecular Design
|
April 27, 1999
A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors
S S So, M Karplus
Journal of Medicinal Chemistry
|
December 20, 1996
Genetic neural networks for quantitative structure-activity relationships: improvements and application of benzodiazepine affinity for benzodiazepine/GABAA receptors
S S So, M Karplus
Journal of Medicinal Chemistry
|
January 22, 1998
Three-dimensional quantitative structure-activity relationships from molecular similarity matrices and genetic neural networks. 2. Applications
S S So, M Karplus
Journal of Computer-Aided Molecular Design
|
November 2, 2001
Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches
S S So, M Karplus
Journal of Chemical Information and Computer Sciences
|
December 26, 2001
Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery. 1. Aqueous solubility
R Liu, S S So
Journal of Medicinal Chemistry
|
March 29, 1996
Evolutionary optimization in quantitative structure-activity relationship: an application of genetic neural networks
S S So, M Karplus
Journal of Medicinal Chemistry
|
August 21, 1992
Application of neural networks: quantitative structure-activity relationships of the derivatives of 2,4-diamino-5-(substituted-benzyl)pyrimidines as DHFR inhibitors
S S So, W G Richards
Journal of Chemical Information and Computer Sciences
|
December 26, 2001
Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery. 2. Blood-brain barrier penetration
R Liu, H Sun, S S So
Proteins
|
October 21, 1998
Use of quantitative structure-property relationships to predict the folding ability of model proteins
A R Dinner, S S So, M Karplus
Page
of 3