Nathan Denlinger
Impact in
- Oncology top 10%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
-
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
Papers in
- Oncology 23
- CAR-T cell therapy research 20
- Co-authors
- Yiping Yang (3 shared papers)Samantha Jaglowski (12 shared papers)David A. Bond (7 shared papers)Narendranath Epperla (9 shared papers)Basem M. William (4 shared papers)Adam S. Kittai (7 shared papers)Ying Huang (5 shared papers)Lindsey Fitzgerald (2 shared papers)
- Journals
- Blood (7 papers)Transplantation and Cellular Therapy (6 papers)Journal of Clinical Oncology (4 papers)Biology of Blood and Marrow Transplantation (2 papers)Blood Advances (2 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Nathan Denlinger
29 papers receiving 372 citations
Peers
Comparison fields: 5 of 52
- Oncology 223
- Immunology 104
- Pathology and Forensic Medicine 50
- Genetics 23
- Hematology 22
Countries citing papers authored by Nathan Denlinger
This map shows the geographic impact of Nathan Denlinger'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 Nathan Denlinger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Denlinger more than expected).
Fields of papers citing papers by Nathan Denlinger
This network shows the impact of papers produced by Nathan Denlinger. 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 Nathan Denlinger. The network helps show where Nathan Denlinger may publish in the future.
Co-authors
The 25 scholars most cited alongside Nathan Denlinger, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 86 | |
| 2 | 2021 | 68 | |
| 3 | 2020 | 41 | |
| 4 | 2014 | 27 | |
| 5 | 2018 | 21 | |
| 6 | 2024 | 21 | |
| 7 | 2020 | 16 | |
| 8 | 2024 | 12 | |
| 9 | 2007 | 11 | |
| 10 | 2018 | 10 | |
| 11 | 2023 | 10 | |
| 12 | 2023 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2024 | 5 | |
| 15 | 2020 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2019 | 3 | |
| 18 | 2020 | 3 | |
| 19 | 2024 | 3 | |
| 20 | 2021 | 2 |
About Nathan Denlinger
Nathan Denlinger is a scholar working on Oncology, Immunology, Molecular Biology, Pathology and Forensic Medicine and Hematology, having authored 33 papers that have together received 375 indexed citations. Recurring topics across this work include CAR-T cell therapy research (20 papers), Lymphoma Diagnosis and Treatment (5 papers), Integrated Circuits and Semiconductor Failure Analysis (3 papers), Acute Myeloid Leukemia Research (3 papers), Endometrial and Cervical Cancer Treatments (3 papers), Chronic Myeloid Leukemia Treatments (3 papers), Chemotherapy-induced cardiotoxicity and mitigation (2 papers) and Cervical Cancer and HPV Research (2 papers). The work is most often cited by research in Oncology (223 citations), Immunology (104 citations), Pathology and Forensic Medicine (50 citations), Genetics (23 citations) and Hematology (22 citations). Nathan Denlinger has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Yiping Yang, Samantha Jaglowski, David A. Bond, Narendranath Epperla, Basem M. William, Adam S. Kittai, Ying Huang, Lindsey Fitzgerald, Agrima Mian and Marcos de Lima. Their work appears in journals such as Blood, Transplantation and Cellular Therapy, Journal of Clinical Oncology, Biology of Blood and Marrow Transplantation and Blood Advances.
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.