Michael D. Bern
Impact in
- Immunology top 5%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- T-cell and B-cell Immunology
- IL-33, ST2, and ILC Pathways
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
- Immunology 11
- Immune Cell Function and Interaction 10
- T-cell and B-cell Immunology 6
- IL-33, ST2, and ILC Pathways 3
- Immunotherapy and Immune Responses 2
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- Cytomegalovirus and herpesvirus research 2
- Co-authors
- Wayne M. Yokoyama (10 shared papers)Kenneth M. Murphy (2 shared papers)Liping Yang (6 shared papers)Theresa L. Murphy (1 shared paper)Karen Adelman (1 shared paper)Ginger W. Muse (1 shared paper)Renee Wu (1 shared paper)Sergei Nechaev (1 shared paper)
- Journals
- eLife (4 papers)The Journal of Experimental Medicine (2 papers)Nature Immunology (2 papers)Cell Reports (1 paper)Blood (1 paper)
- Partner nations
- United StatesJapanRussia
In The Last Decade
Michael D. Bern
13 papers receiving 1.0k citations
Michael D. Bern's Hit Papers
Peers
Comparison fields: 5 of 68
- Immunology 677
- Oncology 266
- Endocrinology 45
- Molecular Biology 341
- Cancer Research 39
Countries citing papers authored by Michael D. Bern
This map shows the geographic impact of Michael D. Bern'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 Michael D. Bern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Bern more than expected).
Fields of papers citing papers by Michael D. Bern
This network shows the impact of papers produced by Michael D. Bern. 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 Michael D. Bern. The network helps show where Michael D. Bern may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael D. Bern, 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 | cDC1 prime and are licensed by CD4+ T cells to induce anti-tumour immunity Hit paper breakdown → | 2020 | 383 |
| 2 | 2013 | 182 | |
| 3 | 2015 | 152 | |
| 4 | 2011 | 125 | |
| 5 | 2019 | 92 | |
| 6 | 2018 | 57 | |
| 7 | 2020 | 23 | |
| 8 | 2017 | 17 | |
| 9 | 2018 | 14 | |
| 10 | 2022 | 13 | |
| 11 | 2024 | 3 | |
| 12 | 2023 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 0 |
About Michael D. Bern
Michael D. Bern is a scholar working on Immunology, Epidemiology, Molecular Biology, Infectious Diseases and Surgery, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (10 papers), T-cell and B-cell Immunology (6 papers), IL-33, ST2, and ILC Pathways (3 papers), Cytomegalovirus and herpesvirus research (2 papers), Immunotherapy and Immune Responses (2 papers), Ubiquitin and proteasome pathways (1 paper), Antifungal resistance and susceptibility (1 paper) and Genomics and Chromatin Dynamics (1 paper). The work is most often cited by research in Immunology (677 citations), Oncology (266 citations), Endocrinology (45 citations), Molecular Biology (341 citations) and Cancer Research (39 citations). Michael D. Bern has collaborated with scholars based in United States, Japan and Russia. Frequent co-authors include Wayne M. Yokoyama, Kenneth M. Murphy, Liping Yang, Theresa L. Murphy, Karen Adelman, Ginger W. Muse, Renee Wu, Sergei Nechaev, Adam Burkholder and Vivek Durai. Their work appears in journals such as eLife, The Journal of Experimental Medicine, Nature Immunology, Cell Reports and Blood.
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.