Chris A. Learn
Impact in
- Genetics top 5%
- Glioma Diagnosis and Treatment
- Immunology top 10%
- Immunotherapy and Immune Responses
Papers in
- Oncology 3
- CAR-T cell therapy research 2
- HER2/EGFR in Cancer Research 1
- Cancer Treatment and Pharmacology 1
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- Immune Response and Inflammation 2
- Biosimilars and Bioanalytical Methods 1
- Co-authors
- John H. Sampson (5 shared papers)Allan H. Friedman (3 shared papers)Roger E. McLendon (2 shared papers)Weihua Xie (3 shared papers)Robert J. Schmittling (3 shared papers)Duane A. Mitchell (1 shared paper)Gary E. Archer (3 shared papers)Henry S. Friedman (2 shared papers)
- Journals
- Clinical Cancer Research (2 papers)Journal of Biological Chemistry (2 papers)Therapeutic Innovation & Regulatory Science (1 paper)Blood (1 paper)Journal of Clinical Oncology (1 paper)
- Partner nations
- United StatesUnited KingdomSerbia
In The Last Decade
Chris A. Learn
9 papers receiving 719 citations
Peers
Comparison fields: 5 of 67
- Genetics 151
- Immunology 222
- Oncology 263
- Epidemiology 207
- Cancer Research 73
Countries citing papers authored by Chris A. Learn
This map shows the geographic impact of Chris A. Learn'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 Chris A. Learn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris A. Learn more than expected).
Fields of papers citing papers by Chris A. Learn
This network shows the impact of papers produced by Chris A. Learn. 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 Chris A. Learn. The network helps show where Chris A. Learn may publish in the future.
Co-authors
The 25 scholars most cited alongside Chris A. Learn, 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 | 322 | |
| 2 | Brain tumors in mice are susceptible to blockade of epidermal growth factor receptor (EGFR) with the oral, specific, EGFR-tyrosine kinase inhibitor ZD1839 (iressa). | 2002 | 146 |
| 3 | 2004 | 136 | |
| 4 | 2006 | 55 | |
| 5 | 2000 | 44 | |
| 6 | 2001 | 28 | |
| 7 | 2006 | 7 | |
| 8 | 2025 | 4 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 0 |
About Chris A. Learn
Chris A. Learn is a scholar working on Oncology, Immunology, Epidemiology, Molecular Biology and Pharmacology, having authored 10 papers that have together received 744 indexed citations. Recurring topics across this work include Immune Response and Inflammation (2 papers), CAR-T cell therapy research (2 papers), HER2/EGFR in Cancer Research (1 paper), S100 Proteins and Annexins (1 paper), Inflammatory mediators and NSAID effects (1 paper), Biosimilars and Bioanalytical Methods (1 paper), Biomedical Ethics and Regulation (1 paper) and Cancer Treatment and Pharmacology (1 paper). The work is most often cited by research in Genetics (151 citations), Immunology (222 citations), Oncology (263 citations), Epidemiology (207 citations) and Cancer Research (73 citations). Chris A. Learn has collaborated with scholars based in United States, United Kingdom and Serbia. Frequent co-authors include John H. Sampson, Allan H. Friedman, Roger E. McLendon, Weihua Xie, Robert J. Schmittling, Duane A. Mitchell, Gary E. Archer, Henry S. Friedman, Darell D. Bigner and Charles E. McCall. Their work appears in journals such as Clinical Cancer Research, Journal of Biological Chemistry, Therapeutic Innovation & Regulatory Science, Blood and Journal of Clinical Oncology.
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.