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Krzysztof Rataj
Krzysztof Rataj
Ardigen S.A
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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, 2016
2752016
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
1942016
Mol-CycleGAN: a generative model for molecular optimization
Ł Maziarka, A Pocha, J Kaczmarczyk, K Rataj, T Danel, M Warchoł
Journal of Cheminformatics 12 (1), 1-18, 2020
1252020
Molecule attention transformer
Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski
arXiv preprint arXiv:2002.08264, 2020
792020
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 45 (5), 2936-2936, 2017
432017
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
422014
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
412018
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
262014
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
222017
Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands
K Rataj, ÁA Kelemen, J Brea, MI Loza, AJ Bojarski, GM Keserű
Molecules 23 (5), 1137, 2018
152018
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), 1-9, 2015
112015
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
112015
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
112015
Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis
K Rataj, W Czarnecki, S Podlewska, A Pocha, AJ Bojarski
Molecules 23 (6), 1242, 2018
72018
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 (1), 1-1, 2013
32013
Molecule-augmented attention transformer
Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski
Workshop on Graph Representation Learning, Neural Information Processing Systems, 2019
12019
The importance of template choice in homology modeling. A 5-HT6R case study
K Rataj, J Witek, S Mordalski, T Kościółek, AJ Bojarski
Journal of Cheminformatics 5 (1), 1-1, 2013
12013
Wpływ wyboru matrycy na jakość modeli homologicznych oraz ich wydajność w procedurze Virtual Screening
K Rataj
2013
Development of the docking protocol in search for inhibitors of Niemann-Pick C1 protein as anti Ebola agents
D Warszycki, R Kafel, K Rataj, V Roy, LA Agrofoglio, AJ Bojarski
Unified Molecule Transformer
Ł Maziarka, T Danel, S Mucha, K Rataj, S Jastrzębski
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