Ben Youngblood
Impact in
- Immunology top 0.2%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Immune cells in cancer
- Oncology top 0.5%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
Papers in
- Immunology 59
- Immune Cell Function and Interaction 54
- T-cell and B-cell Immunology 33
- Immunotherapy and Immune Responses 25
- Immune cells in cancer 6
- Virology 5
- HIV Research and Treatment 5
- Co-authors
- Rafi AhmedHazem E. GhoneimYiping FanHossam A. AbdelsamedKoichi ArakiJ. Scott HalePranay DograCaitlin C. Zebley
- Journals
- The Journal of Immunology (11 papers)Immunity (5 papers)Trends in Immunology (4 papers)Cell Reports (3 papers)Nature (3 papers)
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Ben Youngblood
72 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Immunology 4.4k
- Oncology 2.8k
- Virology 257
- Molecular Biology 1.7k
- Transplantation 56
Countries citing papers authored by Ben Youngblood
This map shows the geographic impact of Ben Youngblood'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 Ben Youngblood with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Youngblood more than expected).
Fields of papers citing papers by Ben Youngblood
This network shows the impact of papers produced by Ben Youngblood. 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 Ben Youngblood. The network helps show where Ben Youngblood may publish in the future.
Co-authors
The 25 scholars most cited alongside Ben Youngblood, 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 | 11 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 15 | |
| 5 | 2024 | 1 | |
| 6 | Functional T cells are capable of supernumerary cell division and longevity Hit paper breakdown → | 2023 | 111 |
| 7 | 2022 | 12 | |
| 8 | 2022 | 36 | |
| 9 | 2020 | 1 | |
| 10 | 2020 | 47 | |
| 11 | 2019 | 59 | |
| 12 | 2019 | 70 | |
| 13 | 2017 | 57 | |
| 14 | 2016 | 73 | |
| 15 | 2013 | 13 | |
| 16 | 2012 | 12 | |
| 17 | 2011 | 111 | |
| 18 | 2010 | 34 | |
| 19 | 2010 | 146 | |
| 20 | 2005 | 11 |
About Ben Youngblood
Ben Youngblood is a scholar working on Immunology, Virology, Oncology, Molecular Biology and Genetics, having authored 77 papers that have together received 6.3k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (54 papers), T-cell and B-cell Immunology (33 papers), Immunotherapy and Immune Responses (25 papers), CAR-T cell therapy research (23 papers), Epigenetics and DNA Methylation (21 papers), Cancer Immunotherapy and Biomarkers (14 papers), Immune cells in cancer (6 papers) and HIV Research and Treatment (5 papers). The work is most often cited by research in Immunology (4.4k citations), Oncology (2.8k citations), Virology (257 citations), Molecular Biology (1.7k citations) and Transplantation (56 citations). Ben Youngblood has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Rafi Ahmed, Hazem E. Ghoneim, Yiping Fan, Hossam A. Abdelsamed, Koichi Araki, J. Scott Hale, Pranay Dogra, Caitlin C. Zebley, Dietmar Zehn and Jeremy M. Boss. Their work appears in journals such as The Journal of Immunology, Immunity, Trends in Immunology, Cell Reports 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.