Daniel L. Barber
- Immunology top 0.05%
- Immune Cell Function and Interaction 34
- T-cell and B-cell Immunology 20
- Immunotherapy and Immune Responses 16
- Immune Response and Inflammation 13
- Immunodeficiency and Autoimmune Disorders 9
- Virology top 0.5%
- Infectious Diseases top 0.2%
- Tuberculosis Research and Epidemiology 32
- Oncology top 0.5%
- Epidemiology top 0.5%
- Mycobacterium research and diagnosis 21
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- Infectious Diseases and Tuberculosis 9
- Co-authors
- Rafi AhmedE. John WherryDavid MasopustArlene H. SharpeGordon J. FreemanBaogong ZhuJames P. AllisonJoseph N. Blattman
- Journals
- The Journal of Immunology (15 papers)Veterinary Record (10 papers)The Journal of Experimental Medicine (7 papers)
- Partner nations
- United StatesUnited KingdomSouth Africa
In The Last Decade
Daniel L. Barber
87 papers receiving 13.7k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Immunology 10.0k
- Virology 938
- Infectious Diseases 3.0k
- Oncology 4.2k
- Epidemiology 3.1k
Countries citing papers authored by Daniel L. Barber
This map shows the geographic impact of Daniel L. Barber'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 Daniel L. Barber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel L. Barber more than expected).
Fields of papers citing papers by Daniel L. Barber
This network shows the impact of papers produced by Daniel L. Barber. 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 Daniel L. Barber. The network helps show where Daniel L. Barber may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel L. Barber, 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 | 2025 | 0 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 12 | |
| 5 | 2023 | 29 | |
| 6 | 2023 | 9 | |
| 7 | 2021 | 39 | |
| 8 | 2019 | 132 | |
| 9 | Rescue of exhausted CD8 T cells by PD-1–targeted therapies is CD28-dependentbreakdown → | 2017 | 724 |
| 10 | 2017 | 57 | |
| 11 | 2010 | 1 | |
| 12 | 2010 | 2 | |
| 13 | 2010 | 372 | |
| 14 | Visualizing Antigen-Specific and\nInfected Cells in Situ Predicts\nOutcomes in Early Viral Infection | 2009 | 155 |
| 15 | 2006 | 294 | |
| 16 | 2006 | 70 | |
| 17 | 2006 | 160 | |
| 18 | 2004 | 408 | |
| 19 | 2003 | 359 | |
| 20 | 2001 | 100 |
About Daniel L. Barber
Daniel L. Barber is a scholar working on Immunology, Infectious Diseases and Virology, having authored 90 papers that have together received 13.9k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (34 papers), Tuberculosis Research and Epidemiology (32 papers), Mycobacterium research and diagnosis (21 papers), T-cell and B-cell Immunology (20 papers), Immunotherapy and Immune Responses (16 papers), Immune Response and Inflammation (13 papers), Immunodeficiency and Autoimmune Disorders (9 papers) and Infectious Diseases and Tuberculosis (9 papers). The work is most often cited by research in Immunology (10.0k citations), Virology (938 citations) and Infectious Diseases (3.0k citations). Daniel L. Barber has collaborated with scholars based in United States, United Kingdom and South Africa. Frequent co-authors include Rafi Ahmed, E. John Wherry, David Masopust, Arlene H. Sharpe, Gordon J. Freeman, Baogong Zhu, James P. Allison, Joseph N. Blattman, Susan M. Kaech and Sang‐Jun Ha. Their work appears in journals such as The Journal of Immunology, Veterinary Record, The Journal of Experimental Medicine, Frontiers in Immunology and Immunity.
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.