Stefan Mordalski
- Molecular Biology top 5%
- Cellular and Molecular Neuroscience top 2%
- Computational Theory and Mathematics top 1%
- Radiology, Nuclear Medicine and Imaging top 5%
- Spectroscopy top 5%
- Co-authors
- David E. GloriamAndrzej J. BojarskiChristian MunkAlexander S. HauserKasper HarpsøeVignir ÍsbergGáspár Pándy‐SzekeresKrzysztof Rataj
- Topics
- Receptor Mechanisms and Signaling (23 papers)Computational Drug Discovery Methods (15 papers)Chemical Synthesis and Analysis (8 papers)
- Partner nations
- PolandDenmarkNetherlands
In The Last Decade
Stefan Mordalski
29 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Molecular Biology 1.5k
- Cellular and Molecular Neuroscience 779
- Computational Theory and Mathematics 380
- Radiology, Nuclear Medicine and Imaging 271
- Spectroscopy 174
Countries citing papers authored by Stefan Mordalski
This map shows the geographic impact of Stefan Mordalski'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 Stefan Mordalski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Mordalski more than expected).
Fields of papers citing papers by Stefan Mordalski
This network shows the impact of papers produced by Stefan Mordalski. 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 Stefan Mordalski. The network helps show where Stefan Mordalski may publish in the future.
Co-authorship network of co-authors of Stefan Mordalski
This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Mordalski. A scholar is included among the top collaborators of Stefan Mordalski 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 Stefan Mordalski. Stefan Mordalski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 13 | |
| 6 | 12 | |
| 7 | 6 | |
| 8 | 16 | |
| 9 | GPCRdb in 2018: adding GPCR structure models and ligandsbreakdown → | 386 |
| 10 | 20 | |
| 11 | 151 | |
| 12 | 365 | |
| 13 | 3 | |
| 14 | 12 | |
| 15 | 359 | |
| 16 | 33 | |
| 17 | 18 | |
| 18 | 29 | |
| 19 | 16 | |
| 20 | 34 |
About Stefan Mordalski
Stefan Mordalski is a scholar working on Computational Theory and Mathematics, Cellular and Molecular Neuroscience and Molecular Biology, having authored 29 papers that have together received 1.8k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (23 papers), Computational Drug Discovery Methods (15 papers) and Chemical Synthesis and Analysis (8 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (779 citations), Computational Theory and Mathematics (380 citations) and Molecular Biology (1.5k citations). Stefan Mordalski has collaborated with scholars based in Poland, Denmark and Netherlands. Frequent co-authors include David E. Gloriam, Andrzej J. Bojarski, Christian Munk, Alexander S. Hauser, Kasper Harpsøe, Vignir Ísberg, Gáspár Pándy‐Szekeres, Krzysztof Rataj, Bas Vroling and Chris de Graaf. Their work appears in journals such as Nucleic Acids Research, PLoS ONE and Trends in Pharmacological Sciences.
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.