Tim Fugmann
Impact in
- Immunology top 10%
- Immunotherapy and Immune Responses
- Molecular Biology top 10%
- vaccines and immunoinformatics approaches
- Lipid Membrane Structure and Behavior
Papers in
-
- vaccines and immunoinformatics approaches 9
- Glycosylation and Glycoproteins Research 3
-
- Monoclonal and Polyclonal Antibodies Research 8
- Co-authors
- Dario Neri (23 shared papers)Danilo Ritz (9 shared papers)Christoph Roesli (10 shared papers)Simone Schmid (1 shared paper)Monilola A. Olayioye (1 shared paper)Klaus Pfizenmaier (1 shared paper)Angelika Haußer (1 shared paper)Kwok‐Kin Wong (1 shared paper)
- Journals
- PROTEOMICS (7 papers)Journal of Proteomics (4 papers)Cancer Research (2 papers)Molecular Cancer Therapeutics (1 paper)Clinical Cancer Research (1 paper)
- Partner nations
- SwitzerlandGermanyJapan
In The Last Decade
Tim Fugmann
28 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 69
- Immunology 358
- Molecular Biology 678
- Oncology 235
- Cell Biology 147
- Radiology, Nuclear Medicine and Imaging 186
Countries citing papers authored by Tim Fugmann
This map shows the geographic impact of Tim Fugmann'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 Tim Fugmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Fugmann more than expected).
Fields of papers citing papers by Tim Fugmann
This network shows the impact of papers produced by Tim Fugmann. 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 Tim Fugmann. The network helps show where Tim Fugmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Fugmann, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 204 | |
| 2 | 2007 | 169 | |
| 3 | 2016 | 78 | |
| 4 | 2009 | 58 | |
| 5 | 2017 | 50 | |
| 6 | 2011 | 50 | |
| 7 | 2016 | 44 | |
| 8 | 2015 | 39 | |
| 9 | 2017 | 39 | |
| 10 | 2009 | 38 | |
| 11 | 2016 | 33 | |
| 12 | 2018 | 27 | |
| 13 | 2018 | 26 | |
| 14 | 2014 | 24 | |
| 15 | 2016 | 24 | |
| 16 | 2010 | 22 | |
| 17 | 2010 | 22 | |
| 18 | 2010 | 18 | |
| 19 | 2016 | 18 | |
| 20 | 2010 | 14 |
About Tim Fugmann
Tim Fugmann is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Immunology, Oncology and Spectroscopy, having authored 29 papers that have together received 1.0k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (9 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), Immunotherapy and Immune Responses (8 papers), Advanced Proteomics Techniques and Applications (6 papers), Biotin and Related Studies (4 papers), Glycosylation and Glycoproteins Research (3 papers), T-cell and B-cell Immunology (3 papers) and CAR-T cell therapy research (3 papers). The work is most often cited by research in Immunology (358 citations), Molecular Biology (678 citations), Oncology (235 citations), Cell Biology (147 citations) and Radiology, Nuclear Medicine and Imaging (186 citations). Tim Fugmann has collaborated with scholars based in Switzerland, Germany and Japan. Frequent co-authors include Dario Neri, Danilo Ritz, Christoph Roesli, Simone Schmid, Monilola A. Olayioye, Klaus Pfizenmaier, Angelika Haußer, Kwok‐Kin Wong, Claire A. Margolis and Harold Pimentel. Their work appears in journals such as PROTEOMICS, Journal of Proteomics, Cancer Research, Molecular Cancer Therapeutics and Clinical Cancer 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.