Jan Byška
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Data Visualization and Analytics
Papers in
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- Protein Structure and Dynamics 13
- Bioinformatics and Genomic Networks 3
- Glycosylation and Glycoproteins Research 2
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- Data Visualization and Analytics 12
- Co-authors
- Barbora Kozlíková (28 shared papers)Adam Jurčík (9 shared papers)Katarína Furmanová (11 shared papers)Jiřı́ Damborský (5 shared papers)Sérgio M. Marques (5 shared papers)David Bednář (5 shared papers)Jan Štourač (3 shared papers)Lukáš Daniel (1 shared paper)
In The Last Decade
Jan Byška
34 papers receiving 540 citations
Jan Byška's Hit Papers
Peers
Comparison fields: 5 of 107
- Biophysics 36
- Computer Vision and Pattern Recognition 126
- Molecular Biology 347
- Human-Computer Interaction 20
- Biotechnology 25
Countries citing papers authored by Jan Byška
This map shows the geographic impact of Jan Byška'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 Jan Byška with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Byška more than expected).
Fields of papers citing papers by Jan Byška
This network shows the impact of papers produced by Jan Byška. 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 Jan Byška. The network helps show where Jan Byška may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Byška, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | CAVER Analyst 2.0: analysis and visualization of channels and tunnels in protein structures and molecular dynamics trajectories Hit paper breakdown → | 2018 | 290 |
| 2 | 2015 | 24 | |
| 3 | 2015 | 23 | |
| 4 | 2023 | 21 | |
| 5 | 2022 | 20 | |
| 6 | 2021 | 19 | |
| 7 | 2017 | 15 | |
| 8 | 2018 | 13 | |
| 9 | 2021 | 12 | |
| 10 | 2019 | 11 | |
| 11 | 2017 | 11 | |
| 12 | 2020 | 10 | |
| 13 | 2017 | 8 | |
| 14 | 2019 | 7 | |
| 15 | 2020 | 6 | |
| 16 | 2022 | 5 | |
| 17 | 2019 | 5 | |
| 18 | 2019 | 5 | |
| 19 | 2015 | 4 | |
| 20 | 2019 | 4 |
About Jan Byška
Jan Byška is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Biophysics, Artificial Intelligence and Spectroscopy, having authored 35 papers that have together received 543 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (13 papers), Data Visualization and Analytics (12 papers), Cell Image Analysis Techniques (6 papers), Mass Spectrometry Techniques and Applications (3 papers), Bioinformatics and Genomic Networks (3 papers), Glycosylation and Glycoproteins Research (2 papers), Business Process Modeling and Analysis (2 papers) and Model-Driven Software Engineering Techniques (2 papers). The work is most often cited by research in Biophysics (36 citations), Computer Vision and Pattern Recognition (126 citations), Molecular Biology (347 citations), Human-Computer Interaction (20 citations) and Biotechnology (25 citations). Jan Byška has collaborated with scholars based in Czechia, Norway and Austria. Frequent co-authors include Barbora Kozlíková, Adam Jurčík, Katarína Furmanová, Jiřı́ Damborský, Sérgio M. Marques, David Bednář, Jan Štourač, Lukáš Daniel, Piia Kokkonen and Martin Maňák. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computers & Graphics, BMC Bioinformatics and Molecular Case Studies.
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.