Mikołaj Żmudziński
- Infectious Diseases top 5%
- Computational Theory and Mathematics top 2%
- Molecular Biology
- Organic Chemistry
- Immunology
- Co-authors
- Marcin DrągWioletta RutScott J. SnipasMiklós BékésTony T. HuangShaun K. OlsenZongyang LvDigant Nayak
- Topics
- SARS-CoV-2 and COVID-19 Research (4 papers)Computational Drug Discovery Methods (3 papers)SARS-CoV-2 detection and testing (2 papers)
- Cited by
- Infectious DiseasesComputational Theory and MathematicsComplementary and alternative medicine
- Partner nations
- PolandUnited StatesGermany
In The Last Decade
Mikołaj Żmudziński
9 papers receiving 695 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Infectious Diseases 394
- Computational Theory and Mathematics 325
- Molecular Biology 282
- Organic Chemistry 115
- Immunology 73
Countries citing papers authored by Mikołaj Żmudziński
This map shows the geographic impact of Mikołaj Żmudziński'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 Mikołaj Żmudziński with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikołaj Żmudziński more than expected).
Fields of papers citing papers by Mikołaj Żmudziński
This network shows the impact of papers produced by Mikołaj Żmudziński. 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 Mikołaj Żmudziński. The network helps show where Mikołaj Żmudziński may publish in the future.
Co-authorship network of co-authors of Mikołaj Żmudziński
This figure shows the co-authorship network connecting the top 25 collaborators of Mikołaj Żmudziński. A scholar is included among the top collaborators of Mikołaj Żmudziński 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 Mikołaj Żmudziński. Mikołaj Żmudziński is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 25 | |
| 3 | 31 | |
| 4 | 7 | |
| 5 | 12 | |
| 6 | 32 | |
| 7 | 212 | |
| 8 | Activity profiling and crystal structures of inhibitor-bound SARS-CoV-2 papain-like protease: A framework for anti–COVID-19 drug designbreakdown → | 353 |
| 9 | 19 |
About Mikołaj Żmudziński
Mikołaj Żmudziński is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Complementary and alternative medicine, having authored 9 papers that have together received 699 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), Computational Drug Discovery Methods (3 papers) and SARS-CoV-2 detection and testing (2 papers). The work is most often cited by research in Infectious Diseases (394 citations), Computational Theory and Mathematics (325 citations) and Complementary and alternative medicine (39 citations). Mikołaj Żmudziński has collaborated with scholars based in Poland, United States and Germany. Frequent co-authors include Marcin Drąg, Wioletta Rut, Scott J. Snipas, Miklós Békés, Tony T. Huang, Shaun K. Olsen, Zongyang Lv, Digant Nayak, Stephanie Patchett and Farid El Oualid. Their work appears in journals such as Scientific Reports, Science Advances and Nature Chemical Biology.
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.