Radoslav Krivák

According to our database, Radoslav Krivák authored at least 10 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

AHoJ: rapid, tailored search and retrieval of apo and holo protein structures for user-defined ligands.

Christos P. Feidakis, Radoslav Krivák, David Hoksza, Marian Novotny

Bioinform., December, 2022

PDBe-KB: collaboratively defining the biological context of structural data.

Mihaly Varadi, Stephen Anyango, David R. Armstrong, John M. Berrisford, Preeti Choudhary, Mandar S. Deshpande, Nurul Nadzirin, Sreenath Nair, Lukás Pravda, Ahsan Tanweer, Bissan Al-Lazikani, Claudia Andreini, Geoffrey J. Barton, David Bednar, Karel Berka, Tom L. Blundell, Kelly Brock, José María Carazo, Jirí Damborský, Alessia David, Sucharita Dey, Roland L. Dunbrack Jr., Juan Fernández-Recio, Franca Fraternali, Toby J. Gibson, Manuela Helmer-Citterich, David Hoksza, Thomas A. Hopf, David Jakubec, Natarajan Kannan, Radoslav Krivák, Manjeet Kumar, Emmanuel D. Levy, Nir London, José Ramón Macías, Mallur Srivatsan Madhusudhan, Debora S. Marks, Lennart Martens, Stuart A McGowan, Jake E. McGreig, Vivek Modi, R. Gonzalo Parra, Gerardo Pepe, Damiano Piovesan, Jaime Prilusky, Valeria Putignano, Leandro G. Radusky, Pathmanaban Ramasamy, Atilio O. Rausch, Nathalie Reuter, Luis A. Rodriguez, Nathan J. Rollins, Antonio Rosato, Pawel Rubach, Luis Serrano, Gulzar Singh, Petr Skoda, Carlos Oscar Sánchez Sorzano, Jan Stourac, Joanna I. Sulkowska, Radka Svobodová Vareková, Natalia Tichshenko, Silvio C. E. Tosatto, Wim F. Vranken, Mark N. Wass, Dandan Xue, Daniel Zaidman, Janet M. Thornton, Michael J. E. Sternberg, Christine A. Orengo, Sameer Velankar

Nucleic Acids Res., 2022

PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures.

David Jakubec, Petr Skoda, Radoslav Krivák, Marian Novotny, David Hoksza

Nucleic Acids Res., 2022

2020

PDBe-KB: a community-driven resource for structural and functional annotations.

Mihaly Varadi, John M. Berrisford, Mandar S. Deshpande, Sreenath Nair, Aleksandras Gutmanas, David R. Armstrong, Lukás Pravda, Bissan Al-Lazikani, Stephen Anyango, Geoffrey J. Barton, Karel Berka, Tom L. Blundell, Neera Borkakoti, Jose M. Dana, Sayoni Das, Sucharita Dey, Patrizio Di Micco, Franca Fraternali, Toby J. Gibson, Manuela Helmer-Citterich, David Hoksza, Liang-Chin Huang, Rishabh Jain, Harry Jubb, Christos C. Kannas, Natarajan Kannan, Jaroslav Koca, Radoslav Krivák, Manjeet Kumar, Emmanuel D. Levy, Fábio Madeira, M. S. Madhusudhan, Henry J. Martell, Stuart A. MacGowan, Jake E. McGreig, Saqib Mir, Abhik Mukhopadhyay, Luca Parca, Typhaine Paysan-Lafosse, Leandro G. Radusky, António J. M. Ribeiro, Luis Serrano, Ian Sillitoe, Gulzar Singh, Petr Skoda, Radka Svobodová Vareková, Jonathan D. Tyzack, Alfonso Valencia, Eloy D. Villasclaras-Fernández, Wim F. Vranken, Mark N. Wass, Janet M. Thornton, Michael J. E. Sternberg, Christine A. Orengo, Sameer Velankar

Nucleic Acids Res., 2020

2019

PrankWeb: a web server for ligand binding site prediction and visualization.

Lukás Jendele, Radoslav Krivák, Petr Skoda, Marian Novotny, David Hoksza

Nucleic Acids Res., 2019

2018

P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure.

Radoslav Krivák, David Hoksza

J. Cheminformatics, 2018

Peptide-Binding Site Prediction From Protein Structure via points on the Solvent Accessible Surface.

Radoslav Krivák, Lukás Jendele, David Hoksza

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017

Improving quality of ligand-binding site prediction with Bayesian optimization.

Radoslav Krivák, David Hoksza, Petr Skoda

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2015

Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features.

Radoslav Krivák, David Hoksza

J. Cheminformatics, 2015

P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features.

Radoslav Krivák, David Hoksza

Proceedings of the Algorithms for Computational Biology, 2015