Krzysztof Rataj
Krzysztof Rataj
Verified email at if-pan.krakow.pl
TitleCited byYear
GPCRdb: an information system for G protein-coupled receptors
V Isberg, S Mordalski, C Munk, K Rataj, K Harpsøe, AS Hauser, B Vroling, ...
Nucleic acids research 44 (D1), D356-D364, 2015
2582015
GPCRdb: the G protein‐coupled receptor database–an introduction
C Munk, V Isberg, S Mordalski, K Harpsøe, K Rataj, AS Hauser, P Kolb, ...
British journal of pharmacology 173 (14), 2195-2207, 2016
902016
Impact of template choice on homology model efficiency in virtual screening
K Rataj, J Witek, S Mordalski, T Kosciolek, AJ Bojarski
Journal of chemical information and modeling 54 (6), 1661-1668, 2014
292014
GPCRdb: an information system for G protein-coupled receptors
V Isberg, S Mordalski, C Munk, K Rataj, K Harpsøe, AS Hauser, B Vroling, ...
Nucleic Acids Res 45, 2936, 2017
192017
An application of machine learning methods to structural interaction fingerprints—a case study of kinase inhibitors
J Witek, S Smusz, K Rataj, S Mordalski, AJ Bojarski
Bioorganic & medicinal chemistry letters 24 (2), 580-585, 2014
192014
From Homology Models to a Set of Predictive Binding Pockets–a 5-HT1A Receptor Case Study
D Warszycki, M Rueda, S Mordalski, K Kristiansen, G Satała, K Rataj, ...
Journal of chemical information and modeling 57 (2), 311-321, 2017
112017
Multiple conformational states in retrospective virtual screening–homology models vs. crystal structures: beta-2 adrenergic receptor case study
S Mordalski, J Witek, S Smusz, K Rataj, AJ Bojarski
Journal of cheminformatics 7 (1), 13, 2015
72015
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
S Smusz, S Mordalski, J Witek, K Rataj, R Kafel, AJ Bojarski
Journal of chemical information and modeling 55 (4), 823-832, 2015
62015
Salt bridge in ligand–protein complexes—systematic theoretical and statistical investigations
R Kurczab, P Śliwa, K Rataj, R Kafel, AJ Bojarski
Journal of Chemical Information and Modeling 58 (11), 2224-2238, 2018
32018
Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis
K Rataj, W Czarnecki, S Podlewska, A Pocha, A Bojarski
Molecules 23 (6), 1242, 2018
32018
Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands
K Rataj, Á Kelemen, J Brea, M Loza, A Bojarski, G Keserű
Molecules 23 (5), 1137, 2018
32018
Mol-CycleGAN-a generative model for molecular optimization
Ł Maziarka, A Pocha, J Kaczmarczyk, K Rataj, M Warchoł
arXiv preprint arXiv:1902.02119, 2019
22019
Application of Structural Interaction Fingerpints (SIFts) into post-docking analysis-insight into activity and selectivity
J Witek, K Rataj, S Mordalski, S Smusz, T Kosciolek, AJ Bojarski
Journal of cheminformatics 5 (S1), P28, 2013
22013
Compounds activity prediction in large imbalanced datasets with substructural relations fingerprint and EEM
WM Czarnecki, K Rataj
2015 IEEE Trustcom/BigDataSE/ISPA 2, 192-192, 2015
12015
The importance of template choice in homology modeling. A 5-HT 6 R case study
K Rataj, J Witek, S Mordalski, T Kościółek, AJ Bojarski
Journal of cheminformatics 5 (1), P8, 2013
2013
A novel machine learning-based protocol for predicting biological activity of chemical compounds
S Smusz, S Mordalski, J Witek, K Rataj, AJ Bojarski
GPCR Workshop, 01-05.12, 2013
2013
Automated docking restrains assignment based on interaction profiles
S Mordalski, J Witek, K Rataj, S Smusz, AJ Bojarski
GPCR Workshop, 01-05.12, 2013
2013
Unified Molecule Transformer
Ł Maziarka, T Danel, S Mucha, K Rataj, S Jastrzębski
2015 IEEE Trustcom/BigDataSE/I? SPA (2015)
WM Czarnecki, K Rataj
Halogen bonding-the role and significance in interactions of ligands with class A GPCRs
R Kurczab, K Rataj, AJ Bojarski
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