Michael D. Bern
Impact in
- Immunology top 5%
- Immunotherapy and Immune Responses
- IL-33, ST2, and ILC Pathways
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Endocrinology top 10%
- Escherichia coli research studies
Papers in
-
- Immune Cell Function and Interaction 5
- IL-33, ST2, and ILC Pathways 2
- T-cell and B-cell Immunology 1
- Immunotherapy and Immune Responses 1
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- NF-κB Signaling Pathways 1
- Co-authors
- Wayne M. Yokoyama (9 shared papers)Kenneth M. Murphy (2 shared papers)Gregory F. Wu (1 shared paper)Robert Schreiber (1 shared paper)Stephen T. Ferris (1 shared paper)William E. Gillanders (1 shared paper)Renee Wu (1 shared paper)Vivek Durai (1 shared paper)
- Journals
- eLife (3 papers)Nature Immunology (2 papers)The Journal of Experimental Medicine (2 papers)Molecular Cell (1 paper)Nature (1 paper)
- Partner nations
- United StatesIsraelRussia
In The Last Decade
Michael D. Bern
12 papers receiving 1.1k citations
Michael D. Bern's Hit Papers
Peers
Comparison fields: 5 of 53
- Immunology 667
- Endocrinology 47
- Oncology 203
- Molecular Biology 252
- Cancer Research 36
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 | 457 |
| 2 | 2013 | 183 | |
| 3 | 2015 | 161 | |
| 4 | 2011 | 130 | |
| 5 | 2019 | 100 | |
| 6 | 2018 | 62 | |
| 7 | 2020 | 23 | |
| 8 | 2017 | 18 | |
| 9 | 2022 | 15 | |
| 10 | 2018 | 13 | |
| 11 | 2023 | 1 | |
| 12 | 2025 | 1 |
About Michael D. Bern
Michael D. Bern is a scholar working on Immunology, Cancer Research, Infectious Diseases, Molecular Biology and Nuclear Energy and Engineering, having authored 12 papers that have together received 1.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (5 papers), IL-33, ST2, and ILC Pathways (2 papers), NF-κB Signaling Pathways (1 paper), T-cell and B-cell Immunology (1 paper), Immunotherapy and Immune Responses (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 (667 citations), Endocrinology (47 citations), Oncology (203 citations), Molecular Biology (252 citations) and Cancer Research (36 citations). Michael D. Bern has collaborated with scholars based in United States, Israel and Russia. Frequent co-authors include Wayne M. Yokoyama, Kenneth M. Murphy, Gregory F. Wu, Robert Schreiber, Stephen T. Ferris, William E. Gillanders, Renee Wu, Vivek Durai, Jeffrey P. Ward and Prachi Bagadia. Their work appears in journals such as eLife, Nature Immunology, The Journal of Experimental Medicine, Molecular Cell and Nature.
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.