Danielle Pinner
Impact in
- Oncology top 2%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
-
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
Papers in
- Oncology 11
- CAR-T cell therapy research 11
-
- Hematopoietic Stem Cell Transplantation 1
- Co-authors
- Paul A. Veys (2 shared papers)Waseem Qasim (2 shared papers)Kimberly Gilmour (2 shared papers)Stuart Paul Adams (2 shared papers)Katie Butler (1 shared paper)Martin Pulé (1 shared paper)Robert Chiesa (1 shared paper)Adrian James Thrasher (1 shared paper)
- Journals
- Blood (4 papers)Science Translational Medicine (3 papers)Nature Medicine (1 paper)Clinical Pharmacology & Therapeutics (1 paper)The Lancet (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Danielle Pinner
11 papers receiving 1.9k citations
Danielle Pinner's Hit Papers
Peers
Comparison fields: 5 of 50
- Oncology 1.4k
- Immunology 128
- Hematology 71
- Molecular Biology 305
- Modeling and Simulation 13
Countries citing papers authored by Danielle Pinner
This map shows the geographic impact of Danielle Pinner'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 Danielle Pinner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Pinner more than expected).
Fields of papers citing papers by Danielle Pinner
This network shows the impact of papers produced by Danielle Pinner. 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 Danielle Pinner. The network helps show where Danielle Pinner may publish in the future.
Co-authors
The 19 scholars most cited alongside Danielle Pinner, 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 | Molecular remission of infant B-ALL after infusion of universal TALEN gene-edited CAR T cells Hit paper breakdown → | 2017 | 773 |
| 2 | Enhanced CAR T cell expansion and prolonged persistence in pediatric patients with ALL treated with a low-affinity CD19 CAR Hit paper breakdown → | 2019 | 512 |
| 3 | 2020 | 306 | |
| 4 | 2022 | 150 | |
| 5 | 2015 | 84 | |
| 6 | 2023 | 59 | |
| 7 | 2019 | 29 | |
| 8 | 2022 | 11 | |
| 9 | 2022 | 4 | |
| 10 | 2025 | 4 | |
| 11 | CD19/CD22 targeting with co-transduced CAR T-cells to prevent antigen negative relapse after CAR T-cell therapy of B-ALL | 2024 | 3 |
| 12 | 2026 | 0 |
About Danielle Pinner
Danielle Pinner is a scholar working on Oncology, Hematology, Nuclear Energy and Engineering, Waste Management and Disposal and Infectious Diseases, having authored 12 papers that have together received 1.9k indexed citations. Recurring topics across this work include CAR-T cell therapy research (11 papers) and Hematopoietic Stem Cell Transplantation (1 paper). The work is most often cited by research in Oncology (1.4k citations), Immunology (128 citations), Hematology (71 citations), Molecular Biology (305 citations) and Modeling and Simulation (13 citations). Danielle Pinner has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Paul A. Veys, Waseem Qasim, Kimberly Gilmour, Stuart Paul Adams, Katie Butler, Martin Pulé, Robert Chiesa, Adrian James Thrasher, Hong Zhan and Sujith Samarasinghe. Their work appears in journals such as Blood, Science Translational Medicine, Nature Medicine, Clinical Pharmacology & Therapeutics and The Lancet.
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.