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Ligand binding sites
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Person
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doc. RNDr. David Hoksza Ph.D.
Academic staff at Faculty of Mathematics and Physics
2 study programmes
4 classes
97 publications
Study programme
programme
Bioinformatics and computational biology
+1
🇨🇿 PhD. |
Faculty of Mathematics and Physics
Classes
class
Data Visualization Techniques
NDBI042 |
Faculty of Mathematics and Physics
class
Algorithms, databases and tools in bioinformatics
NDBI044 |
Faculty of Mathematics and Physics
class
Project in bioinformatics
NPRG061 |
Faculty of Mathematics and Physics
class
Doctoral bioinformatics seminar
NSWI201 |
Faculty of Mathematics and Physics
Publications
publication
P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure
2018 |
Faculty of Mathematics and Physics
publication
Improving quality of ligand-binding site prediction with Bayesian optimization
2017 |
Faculty of Mathematics and Physics
publication
Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features
2015 |
Faculty of Mathematics and Physics
publication
P2RANK: knowledge-based ligand binding site prediction using aggregated local features
2015 |
Faculty of Mathematics and Physics
publication
P2RANK
Publication without faculty affiliation
publication
Visualizations for universal deep-feature representations: survey and taxonomy
2024 |
Faculty of Mathematics and Physics
publication
Cryptic binding site prediction with protein language models
2023 |
Faculty of Mathematics and Physics, Faculty of Science
publication
Visualization of automatically combined disease maps and pathway diagrams for rare diseases
2023 |
Faculty of Mathematics and Physics
publication
Visual Representations for Data Analytics: User Study
2023 |
Faculty of Mathematics and Physics
publication
Framework for Protein Structures Conformation Analysis
2023 |
Faculty of Mathematics and Physics
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