Evaluation of different machine learning methods for ligand-based virtual screening. - Rafal Kurczab; Sabina Smusz; Andrzej J. Bojarski (J. Cheminformatics, 2011)

The influence of training actives/inactives ratio on machine learning performance. - Rafal Kurczab; Sabina Smusz; Andrzej J. Bojarski (J. Cheminformatics, 2013)

The influence of the inactives subset generation on the performance of machine learning methods. - Sabina Smusz; Rafal Kurczab; Andrzej J. Bojarski (J. Cheminformatics, 2013)

The influence of hashed fingerprints density on the machine learning methods performance. - Sabina Smusz; Rafal Kurczab; Andrzej J. Bojarski (J. Cheminformatics, 2013)

New Strategy for Receptor-Based Pharmacophore Query Construction: A Case Study for 5-HT7 Receptor Ligands. - Rafal Kurczab; Andrzej J. Bojarski (J. Chem. Inf. Model., 2013)

The influence of negative training set size on machine learning-based virtual screening. - Rafal Kurczab; Sabina Smusz; Andrzej J. Bojarski (J. Cheminformatics, 2014)

Identification of Novel Serotonin Transporter Compounds by Virtual Screening. - Mari Gabrielsen; Rafal Kurczab; Agata Siwek; Malgorzata Wolak; Aina Westrheim Ravna; Kurt Kristiansen; Irina Kufareva; Ruben Abagyan; Gabriel Nowak; Zdzislaw Chilmonczyk; Ingebrigt Sylte; Andrzej J. Bojarski (J. Chem. Inf. Model., 2014)

Salt Bridge in Ligand-Protein Complexes - Systematic Theoretical and Statistical Investigations. - Rafal Kurczab; Pawel Sliwa; Krzysztof Rataj; Rafal Kafel; Andrzej J. Bojarski (J. Chem. Inf. Model., 2018)

2D SIFt: a matrix of ligand-receptor interactions. - Stefan Mordalski; Agnieszka Wojtuch; Igor T. Podolak; Rafal Kurczab; Andrzej J. Bojarski (J. Cheminformatics, 2021)

Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design. - Dawid Warszycki; Lukasz Struski; Marek Smieja; Rafal Kafel; Rafal Kurczab (J. Chem. Inf. Model., 2021)

PluGeN: Multi-Label Conditional Generation from Pre-trained Models. - Maciej Wolczyk; Magdalena Proszewska; Lukasz Maziarka; Maciej Zieba; Patryk Wielopolski; Rafal Kurczab; Marek Smieja (AAAI, 2022)

From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties. - Arkadiusz Leniak; Wojciech Pietrus; Rafal Kurczab (J. Chem. Inf. Model., 2024)

From NMR to AI: Do We Need 1H NMR Experimental Spectra to Obtain High-Quality logD Prediction Models? - Arkadiusz Leniak; Wojciech Pietrus; Aleksandra Swiderska; Rafal Kurczab (J. Chem. Inf. Model., 2025)