Tim Fugmann
Impact in
- Immunology top 10%
- Immunotherapy and Immune Responses
- Molecular Biology top 10%
- vaccines and immunoinformatics approaches
- RNA modifications and cancer
- Lipid Membrane Structure and Behavior
Papers in
-
- Monoclonal and Polyclonal Antibodies Research 11
-
- Immunotherapy and Immune Responses 8
- Co-authors
- Dario NeriDanilo RitzChristoph RoesliSimone SchmidMonilola A. OlayioyeAngelika HaußerKlaus PfizenmaierMeng Xiao He
- 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 72
- Immunology 374
- Molecular Biology 698
- Oncology 249
- Cell Biology 149
- Radiology, Nuclear Medicine and Imaging 198
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 6 | |
| 2 | 2019 | 13 | |
| 3 | HLA-C restricted neoepitopes contribute significantly to the immune recognition of cancer | 2019 | 1 |
| 4 | 2018 | 26 | |
| 5 | 2018 | 194 | |
| 6 | 2017 | 49 | |
| 7 | 2016 | 75 | |
| 8 | 2016 | 43 | |
| 9 | 2016 | 24 | |
| 10 | 2014 | 23 | |
| 11 | 2014 | 1 | |
| 12 | 2011 | 8 | |
| 13 | 2011 | 49 | |
| 14 | 2010 | 16 | |
| 15 | 2010 | 14 | |
| 16 | 2010 | 22 | |
| 17 | 2010 | 22 | |
| 18 | 2009 | 36 | |
| 19 | 2009 | 9 | |
| 20 | 2007 | 167 |
About Tim Fugmann
Tim Fugmann is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology, Spectroscopy, Immunology and Allergy and Molecular Biology, having authored 28 papers that have together received 1.0k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (11 papers), vaccines and immunoinformatics approaches (9 papers), Immunotherapy and Immune Responses (8 papers), Advanced Proteomics Techniques and Applications (6 papers), Glycosylation and Glycoproteins Research (4 papers), CAR-T cell therapy research (3 papers), Biotin and Related Studies (3 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Immunology (374 citations), Molecular Biology (698 citations), Oncology (249 citations), Cell Biology (149 citations) and Radiology, Nuclear Medicine and Imaging (198 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, Angelika Haußer, Klaus Pfizenmaier, Meng Xiao He, Diana Miao and Claire A. Margolis. 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.