Dawson Knoblock
Impact in
- Immunology top 10%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- T-cell and B-cell Immunology
- Immune cells in cancer
- IL-33, ST2, and ILC Pathways
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- Pancreatic and Hepatic Oncology Research
- CAR-T cell therapy research
Papers in
- Oncology 5
- Cancer Immunotherapy and Biomarkers 4
- CAR-T cell therapy research 3
- Peptidase Inhibition and Analysis 1
- Pancreatic and Hepatic Oncology Research 1
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- Cervical Cancer and HPV Research 2
- Co-authors
- Stephen C. Blacklow (1 shared paper)Yumi Yashiro–Ohtani (1 shared paper)Cristina Del Bianco (1 shared paper)Terry Fang (1 shared paper)Warren S. Pear (1 shared paper)Gregory L. Beatty (2 shared papers)Whitney L. Gladney (1 shared paper)Rafael Winograd (1 shared paper)
- Journals
- Blood (2 papers)Clinical Cancer Research (1 paper)Cancer Immunology Immunotherapy (1 paper)Vaccines (1 paper)HemaSphere (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Dawson Knoblock
8 papers receiving 690 citations
Peers
Comparison fields: 5 of 64
- Immunology 403
- Oncology 337
- Cancer Research 69
- Biotechnology 25
- Molecular Biology 194
Countries citing papers authored by Dawson Knoblock
This map shows the geographic impact of Dawson Knoblock'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 Dawson Knoblock with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawson Knoblock more than expected).
Fields of papers citing papers by Dawson Knoblock
This network shows the impact of papers produced by Dawson Knoblock. 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 Dawson Knoblock. The network helps show where Dawson Knoblock may publish in the future.
Co-authors
The 25 scholars most cited alongside Dawson Knoblock, 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 | 2007 | 304 | |
| 2 | 2015 | 228 | |
| 3 | 2017 | 84 | |
| 4 | 2017 | 34 | |
| 5 | 2020 | 20 | |
| 6 | 2020 | 16 | |
| 7 | 2022 | 8 | |
| 8 | 2023 | 1 |
About Dawson Knoblock
Dawson Knoblock is a scholar working on Oncology, Epidemiology, Hematology, Immunology and Infectious Diseases, having authored 8 papers that have together received 695 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (4 papers), CAR-T cell therapy research (3 papers), Cervical Cancer and HPV Research (2 papers), Multiple Myeloma Research and Treatments (2 papers), Peptidase Inhibition and Analysis (1 paper), Lung Cancer Diagnosis and Treatment (1 paper), Neuroinflammation and Neurodegeneration Mechanisms (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Immunology (403 citations), Oncology (337 citations), Cancer Research (69 citations), Biotechnology (25 citations) and Molecular Biology (194 citations). Dawson Knoblock has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Stephen C. Blacklow, Yumi Yashiro–Ohtani, Cristina Del Bianco, Terry Fang, Warren S. Pear, Gregory L. Beatty, Whitney L. Gladney, Rafael Winograd, Robert H. Vonderheide and Kristen B. Long. Their work appears in journals such as Blood, Clinical Cancer Research, Cancer Immunology Immunotherapy, Vaccines and HemaSphere.
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.