Publications
- PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures2022 | Faculty of Mathematics and Physics, Faculty of Science
- AHoJ: rapid, tailored search and retrieval of apo and holo protein structures for user-defined ligands2022 | Faculty of Mathematics and Physics, Faculty of Science
- PrankWeb: a web server for ligand binding site prediction and visualization2019 | Faculty of Mathematics and Physics, Faculty of Science
- Towards universal platform for protein binding site prediction2018 | Faculty of Mathematics and Physics, Faculty of Science
- P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure2018 | Faculty of Mathematics and Physics
- Improving quality of ligand-binding site prediction with Bayesian optimization2017 | Faculty of Mathematics and Physics
- Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features2015 | Faculty of Mathematics and Physics
- P2RANK: knowledge-based ligand binding site prediction using aggregated local features2015 | Faculty of Mathematics and Physics
- P2RANKPublication without faculty affiliation
- PDBe-KB: collaboratively defining the biological context of structural data2022 | Faculty of Mathematics and Physics
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