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Marián Gall

Showing results (1-10 of 6) with videos related to

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The Journal of Physical Chemistry. B|May 11, 2024
SchNetPack Hyperparameter Optimization for a More Reliable Top Docking Scores PredictionJán Matúška, Lukas Bucinsky, Marián Gall, et al.
Journal of Computational Chemistry|December 6, 2019
Coordination bonding in dicopper and dichromium tetrakis(μ-acetato)-diaqua complexes: Nature, strength, length, and topologyMichal Malček, Barbora Vénosová, Ingrid Puškárová, et al.
The Journal of Physical Chemistry. B|March 20, 2026
Ligand Conformational Variability Enhances Machine Learning Prediction of Protein-Ligand Binding AffinityÁdám Lévárdi, Ján Matúška, Lukas Bucinsky, et al.
Biophysical Chemistry|July 10, 2022
Molecular docking and machine learning affinity prediction of compounds identified upon softwood bark extraction to the main protease of the SARS-CoV-2 virusMichal Jablonský, Marek Štekláč, Veronika Majová, et al.
Computational Biology and Chemistry|March 15, 2022
Machine learning prediction of 3CL<sup>pro</sup> SARS-CoV-2 docking scoresLukas Bucinsky, Dušan Bortňák, Marián Gall, et al.
Scientific Reports|October 1, 2021
Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiologyNaďa Krivoňáková, Andrea Šoltýsová, Michal Tamáš, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
The Journal of Physical Chemistry. B|May 11, 2024
SchNetPack Hyperparameter Optimization for a More Reliable Top Docking Scores PredictionJán Matúška, Lukas Bucinsky, Marián Gall, et al.
Journal of Computational Chemistry|December 6, 2019
Coordination bonding in dicopper and dichromium tetrakis(μ-acetato)-diaqua complexes: Nature, strength, length, and topologyMichal Malček, Barbora Vénosová, Ingrid Puškárová, et al.
The Journal of Physical Chemistry. B|March 20, 2026
Ligand Conformational Variability Enhances Machine Learning Prediction of Protein-Ligand Binding AffinityÁdám Lévárdi, Ján Matúška, Lukas Bucinsky, et al.
Biophysical Chemistry|July 10, 2022
Molecular docking and machine learning affinity prediction of compounds identified upon softwood bark extraction to the main protease of the SARS-CoV-2 virusMichal Jablonský, Marek Štekláč, Veronika Majová, et al.
Computational Biology and Chemistry|March 15, 2022
Machine learning prediction of 3CL<sup>pro</sup> SARS-CoV-2 docking scoresLukas Bucinsky, Dušan Bortňák, Marián Gall, et al.
Scientific Reports|October 1, 2021
Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiologyNaďa Krivoňáková, Andrea Šoltýsová, Michal Tamáš, et al.
Pageof 1