ℹ️
🇬🇧
Search
Search for people relevant for "Protein pockets"
Protein pockets
Person
Class
Person
Publication
Programmes
Export current view
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 protein-ligand binding site prediction accuracy by classification of inner pocket points using local features
2015 |
Faculty of Mathematics and Physics
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
publication
PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures
2022 |
Faculty of Mathematics and Physics, Faculty of Science
publication
AHoJ: rapid, tailored search and retrieval of apo and holo protein structures for user-defined ligands
2022 |
Faculty of Mathematics and Physics, Faculty of Science
publication
Machine and human interpretable patient visualizations
2022 |
Faculty of Mathematics and Physics, First Faculty of Medicine
Load more publications (87)
Loading network view...