Vlado Dančík
- Molecular Biology top 5%
- Spectroscopy top 1%
- Pulmonary and Respiratory Medicine top 5%
- Cancer Research top 5%
- Computational Theory and Mathematics top 1%
- Co-authors
- Paul A. ClemonsBridget K. WagnerMonica SchenonePavel A. PevznerJames E. VathKarl R. ClauserTheresa A. AddonaStuart L. Schreiber
- Topics
- Computational Drug Discovery Methods (9 papers)Protein Structure and Dynamics (7 papers)Mass Spectrometry Techniques and Applications (5 papers)
- Journals
- CellProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesSlovakiaAustria
In The Last Decade
Vlado Dančík
39 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Molecular Biology 2.3k
- Spectroscopy 598
- Pulmonary and Respiratory Medicine 537
- Cancer Research 463
- Computational Theory and Mathematics 437
Countries citing papers authored by Vlado Dančík
This map shows the geographic impact of Vlado Dančík'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 Vlado Dančík with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vlado Dančík more than expected).
Fields of papers citing papers by Vlado Dančík
This network shows the impact of papers produced by Vlado Dančík. 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 Vlado Dančík. The network helps show where Vlado Dančík may publish in the future.
Co-authorship network of co-authors of Vlado Dančík
This figure shows the co-authorship network connecting the top 25 collaborators of Vlado Dančík. A scholar is included among the top collaborators of Vlado Dančík 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 Vlado Dančík. Vlado Dančík is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 40 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 30 | |
| 5 | A GPX4-dependent cancer cell state underlies the clear-cell morphology and confers sensitivity to ferroptosisbreakdown → | 663 |
| 6 | 150 | |
| 7 | 82 | |
| 8 | 20 | |
| 9 | 17 | |
| 10 | Target identification and mechanism of action in chemical biology and drug discoverybreakdown → | 745 |
| 11 | 58 | |
| 12 | 24 | |
| 13 | 10 | |
| 14 | 90 | |
| 15 | 422 | |
| 16 | 10 | |
| 17 | 3 | |
| 18 | 5 | |
| 19 | 36 | |
| 20 | 7 |
About Vlado Dančík
Vlado Dančík is a scholar working on Computational Theory and Mathematics, Biophysics and Molecular Biology, having authored 39 papers that have together received 3.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Protein Structure and Dynamics (7 papers) and Mass Spectrometry Techniques and Applications (5 papers). The work is most often cited by research in Spectroscopy (598 citations), Molecular Biology (2.3k citations) and Cancer Research (463 citations). Vlado Dančík has collaborated with scholars based in United States, Slovakia and Austria. Frequent co-authors include Paul A. Clemons, Bridget K. Wagner, Monica Schenone, Pavel A. Pevzner, James E. Vath, Karl R. Clauser, Theresa A. Addona, Stuart L. Schreiber, Elizaveta S. Leshchiner and Amy Deik. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.