David Hoksza
- Molecular Biology top 10%
- Computational Theory and Mathematics top 1%
- Materials Chemistry
- Genetics
- Organic Chemistry
- Co-authors
- Radoslav KrivákPetr ŠkodaMarián NovotnýLukáš JendeleDaniel SvozilDávid JakubecReinhard SchneiderPetr Čech
- Topics
- Computational Drug Discovery Methods (21 papers)Protein Structure and Dynamics (20 papers)RNA and protein synthesis mechanisms (14 papers)
- Partner nations
- CzechiaLuxembourgUnited States
In The Last Decade
David Hoksza
51 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 811
- Computational Theory and Mathematics 407
- Materials Chemistry 125
- Genetics 80
- Organic Chemistry 69
Countries citing papers authored by David Hoksza
This map shows the geographic impact of David Hoksza's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Hoksza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Hoksza more than expected).
Fields of papers citing papers by David Hoksza
This network shows the impact of papers produced by David Hoksza. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Hoksza. The network helps show where David Hoksza may publish in the future.
Co-authorship network of co-authors of David Hoksza
This figure shows the co-authorship network connecting the top 25 collaborators of David Hoksza. A scholar is included among the top collaborators of David Hoksza based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Hoksza. David Hoksza is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 77 | |
| 8 | PrankWeb: a web server for ligand binding site prediction and visualizationbreakdown → | 276 |
| 9 | 14 | |
| 10 | P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structurebreakdown → | 296 |
| 11 | 5 | |
| 12 | 20 | |
| 13 | 2 | |
| 14 | 54 | |
| 15 | 10 | |
| 16 | 22 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 5 | |
| 20 | Index-Based Approach to Similarity Search in Protein and Nucleotide Databases | 4 |
About David Hoksza
David Hoksza is a scholar working on Computational Theory and Mathematics, Molecular Biology and Spectroscopy, having authored 55 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (21 papers), Protein Structure and Dynamics (20 papers) and RNA and protein synthesis mechanisms (14 papers). The work is most often cited by research in Computational Theory and Mathematics (407 citations), Molecular Biology (811 citations) and Pharmacology (50 citations). David Hoksza has collaborated with scholars based in Czechia, Luxembourg and United States. Frequent co-authors include Radoslav Krivák, Petr Škoda, Marián Novotný, Lukáš Jendele, Daniel Svozil, Dávid Jakubec, Reinhard Schneider, Petr Čech, Jan Jelı́nek and Marek Ostaszewski. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.