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High-accuracy
Person
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Person
Publication
Programmes
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
On Comparison of SimTandem with State-of-the-Art Peptide Identification Tools, Efficiency of Precursor Mass Filter and Dealing with Variable Modifications
2013 |
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
publication
PDBe-KB: collaboratively defining the biological context of structural data
2022 |
Faculty of Mathematics and Physics
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