Frédérick Masson
Impact in
- Immunology top 1%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- IL-33, ST2, and ILC Pathways
- Immune cells in cancer
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
- Immunology 29
- T-cell and B-cell Immunology 22
- Immune Cell Function and Interaction 18
- Immunotherapy and Immune Responses 15
- IL-33, ST2, and ILC Pathways 3
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- Neuroinflammation and Neurodegeneration Mechanisms 5
- Co-authors
- Gabrielle T. BelzAxel KalliesStephen L. NuttAnnie XinGordon K. SmythLisa A. MielkeWei ShiMeinrad Busslinger
- Journals
- The Journal of Immunology (6 papers)Immunity (3 papers)Science Translational Medicine (2 papers)Nature Immunology (2 papers)Cancer Immunology Research (2 papers)
- Partner nations
- AustraliaSwitzerlandFrance
In The Last Decade
Frédérick Masson
37 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 103
- Immunology 2.0k
- Oncology 762
- Neurology 132
- Cancer Research 197
- Genetics 131
Countries citing papers authored by Frédérick Masson
This map shows the geographic impact of Frédérick Masson'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 Frédérick Masson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédérick Masson more than expected).
Fields of papers citing papers by Frédérick Masson
This network shows the impact of papers produced by Frédérick Masson. 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 Frédérick Masson. The network helps show where Frédérick Masson may publish in the future.
Co-authors
The 25 scholars most cited alongside Frédérick Masson, 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 | 2025 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 7 | |
| 4 | 2022 | 16 | |
| 5 | 2021 | 29 | |
| 6 | 2021 | 22 | |
| 7 | 2020 | 2 | |
| 8 | 2018 | 34 | |
| 9 | A combinatorial threshold model for effector differentiation of CD8( ) T cells mediated by Blimp-1 and T-bet | 2016 | 0 |
| 10 | 2016 | 126 | |
| 11 | 2016 | 26 | |
| 12 | 2013 | 77 | |
| 13 | 2012 | 33 | |
| 14 | 2011 | 110 | |
| 15 | 2011 | 473 | |
| 16 | 2010 | 51 | |
| 17 | 2010 | 15 | |
| 18 | 2008 | 23 | |
| 19 | 2005 | 186 | |
| 20 | 2003 | 51 |
About Frédérick Masson
Frédérick Masson is a scholar working on Immunology, Neurology, Oncology, Cancer Research and Virology, having authored 39 papers that have together received 2.7k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (18 papers), Immunotherapy and Immune Responses (15 papers), CAR-T cell therapy research (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers), IL-33, ST2, and ILC Pathways (3 papers), Cytokine Signaling Pathways and Interactions (2 papers) and Acute Myeloid Leukemia Research (2 papers). The work is most often cited by research in Immunology (2.0k citations), Oncology (762 citations), Neurology (132 citations), Cancer Research (197 citations) and Genetics (131 citations). Frédérick Masson has collaborated with scholars based in Australia, Switzerland and France. Frequent co-authors include Gabrielle T. Belz, Axel Kallies, Stephen L. Nutt, Annie Xin, Gordon K. Smyth, Lisa A. Mielke, Wei Shi, Meinrad Busslinger, Martina Minnich and Yoelsis Garcia‐Mayea. Their work appears in journals such as The Journal of Immunology, Immunity, Science Translational Medicine, Nature Immunology and Cancer Immunology 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.