Andrzej J. Bojarski

According to our database1, Andrzej J. Bojarski authored at least 20 papers between 2011 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
GPCRdb in 2018: adding GPCR structure models and ligands.
Nucleic Acids Research, 2018

2017
From Homology Models to a Set of Predictive Binding Pockets-a 5-HT1A Receptor Case Study.
Journal of Chemical Information and Modeling, 2017

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.
Journal of Chemical Information and Modeling, 2017

2016
GPCRdb: an information system for G protein-coupled receptors.
Nucleic Acids Research, 2016

2015
Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods - A Case Study of Serotonin Receptors 5-HT6 and 5-HT7.
Journal of Chemical Information and Modeling, 2015

Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes.
Journal of Chemical Information and Modeling, 2015

Multiple conformational states in retrospective virtual screening - homology models vs. crystal structures: beta-2 adrenergic receptor case study.
J. Cheminformatics, 2015

Robust optimization of SVM hyperparameters in the classification of bioactive compounds.
J. Cheminformatics, 2015

2014
Impact of Template Choice on Homology Model Efficiency in Virtual Screening.
Journal of Chemical Information and Modeling, 2014

Identification of Novel Serotonin Transporter Compounds by Virtual Screening.
Journal of Chemical Information and Modeling, 2014

The influence of negative training set size on machine learning-based virtual screening.
J. Cheminformatics, 2014

2013
New Strategy for Receptor-Based Pharmacophore Query Construction: A Case Study for 5-HT7 Receptor Ligands.
Journal of Chemical Information and Modeling, 2013

Application of Structural Interaction Fingerpints (SIFts) into post-docking analysis - insight into activity and selectivity.
J. Cheminformatics, 2013

The influence of hashed fingerprints density on the machine learning methods performance.
J. Cheminformatics, 2013

The influence of the inactives subset generation on the performance of machine learning methods.
J. Cheminformatics, 2013

The importance of template choice in homology modeling. A 5-HT6R case study.
J. Cheminformatics, 2013

The influence of training actives/inactives ratio on machine learning performance.
J. Cheminformatics, 2013

2011
Homology modelling of metabotropic glutamate receptor 2.
J. Cheminformatics, 2011

Evaluation of different machine learning methods for ligand-based virtual screening.
J. Cheminformatics, 2011

Rapid binding site analysis by means of structural interaction fingerprint patterns - an implication to GPCR-targeted CADD.
J. Cheminformatics, 2011


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