David Gfeller
- Molecular Biology top 2%
- Immunology top 0.5%
- Oncology top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Computational Theory and Mathematics top 0.5%
- Co-authors
- Vincent ZoeteOlivier MichielinJulien RacleDaniel E. SpeiserMichal Bassani‐SternbergAurélien GrosdidierMatthias WirthAntoine Daina
- Topics
- vaccines and immunoinformatics approaches (28 papers)Immunotherapy and Immune Responses (22 papers)Monoclonal and Polyclonal Antibodies Research (15 papers)
- Cited by
- ImmunologyOncologyMolecular Biology
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersNucleic Acids Research
- Partner nations
- SwitzerlandUnited StatesCanada
In The Last Decade
David Gfeller
71 papers receiving 6.8k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Molecular Biology 3.8k
- Immunology 2.6k
- Oncology 2.0k
- Radiology, Nuclear Medicine and Imaging 671
- Computational Theory and Mathematics 652
Countries citing papers authored by David Gfeller
This map shows the geographic impact of David Gfeller'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 Gfeller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Gfeller more than expected).
Fields of papers citing papers by David Gfeller
This network shows the impact of papers produced by David Gfeller. 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 Gfeller. The network helps show where David Gfeller may publish in the future.
Co-authorship network of co-authors of David Gfeller
This figure shows the co-authorship network connecting the top 25 collaborators of David Gfeller. A scholar is included among the top collaborators of David Gfeller 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 Gfeller. David Gfeller 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 | 2 | |
| 3 | 13 | |
| 4 | 14 | |
| 5 | 75 | |
| 6 | 101 | |
| 7 | 48 | |
| 8 | 91 | |
| 9 | 42 | |
| 10 | 200 | |
| 11 | 35 | |
| 12 | 16 | |
| 13 | 74 | |
| 14 | 8 | |
| 15 | 177 | |
| 16 | 100 | |
| 17 | 28 | |
| 18 | 97 | |
| 19 | 59 | |
| 20 | Synonym Dictionary Improvement through Markov Clustering and Clustering Stability | 11 |
About David Gfeller
David Gfeller is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 73 papers that have together received 6.8k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (28 papers), Immunotherapy and Immune Responses (22 papers) and Monoclonal and Polyclonal Antibodies Research (15 papers). The work is most often cited by research in Immunology (2.6k citations), Oncology (2.0k citations) and Molecular Biology (3.8k citations). David Gfeller has collaborated with scholars based in Switzerland, United States and Canada. Frequent co-authors include Vincent Zoete, Olivier Michielin, Julien Racle, Daniel E. Speiser, Michal Bassani‐Sternberg, Aurélien Grosdidier, Matthias Wirth, Antoine Daina, Petra Baumgaertner and Kaat de Jonge. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nucleic Acids Research.
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.