Nir Friedman
Impact in
- Immunology top 2%
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Aging top 5%
Papers in
- Immunology 32
- T-cell and B-cell Immunology 28
- Immunotherapy and Immune Responses 9
- Oncology 6
- Cancer Immunotherapy and Biomarkers 4
- CAR-T cell therapy research 2
- Co-authors
- Eric Shifrut (13 shared papers)Shlomit Reich-Zeliger (17 shared papers)Nili Tickotsky (1 shared paper)Jaime Prilusky (1 shared paper)Nir Davidson (5 shared papers)Ariel Kaplan (3 shared papers)Benny Chain (10 shared papers)Irina Zaretsky (7 shared papers)
- Journals
- Frontiers in Immunology (7 papers)Proceedings of the National Academy of Sciences (4 papers)Bioinformatics (3 papers)Journal of Clinical Investigation (2 papers)eLife (2 papers)
- Partner nations
- IsraelUnited KingdomUnited States
In The Last Decade
Nir Friedman
46 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 107
- Immunology 1k
- Aging 44
- Neurology 171
- Oncology 365
- Molecular Biology 812
Countries citing papers authored by Nir Friedman
This map shows the geographic impact of Nir Friedman'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 Nir Friedman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nir Friedman more than expected).
Fields of papers citing papers by Nir Friedman
This network shows the impact of papers produced by Nir Friedman. 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 Nir Friedman. The network helps show where Nir Friedman may publish in the future.
Co-authors
The 25 scholars most cited alongside Nir Friedman, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 378 | |
| 2 | 2013 | 254 | |
| 3 | 2019 | 228 | |
| 4 | 2001 | 166 | |
| 5 | 2019 | 146 | |
| 6 | 2017 | 118 | |
| 7 | 2019 | 94 | |
| 8 | 2014 | 89 | |
| 9 | 2013 | 85 | |
| 10 | 2018 | 84 | |
| 11 | 2012 | 83 | |
| 12 | 2014 | 78 | |
| 13 | 2016 | 68 | |
| 14 | 2016 | 68 | |
| 15 | 2012 | 67 | |
| 16 | 2012 | 62 | |
| 17 | 2018 | 61 | |
| 18 | 2017 | 54 | |
| 19 | 2019 | 54 | |
| 20 | 2021 | 51 |
About Nir Friedman
Nir Friedman is a scholar working on Immunology, Oncology, Molecular Biology, Cell Biology and Atomic and Molecular Physics, and Optics, having authored 46 papers that have together received 2.8k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (28 papers), Immunotherapy and Immune Responses (9 papers), Cancer Immunotherapy and Biomarkers (4 papers), Gene Regulatory Network Analysis (4 papers), Cellular Mechanics and Interactions (3 papers), vaccines and immunoinformatics approaches (3 papers), Cold Atom Physics and Bose-Einstein Condensates (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Immunology (1k citations), Aging (44 citations), Neurology (171 citations), Oncology (365 citations) and Molecular Biology (812 citations). Nir Friedman has collaborated with scholars based in Israel, United Kingdom and United States. Frequent co-authors include Eric Shifrut, Shlomit Reich-Zeliger, Nili Tickotsky, Jaime Prilusky, Nir Davidson, Ariel Kaplan, Benny Chain, Irina Zaretsky, Inbal Eizenberg-Magar and Hilah Gal. Their work appears in journals such as Frontiers in Immunology, Proceedings of the National Academy of Sciences, Bioinformatics, Journal of Clinical Investigation and eLife.
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.