Kevin Barton
Impact in
- Immunology top 2%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Hematology top 2%
- Multiple Myeloma Research and Treatments
- Acute Myeloid Leukemia Research
Papers in
-
- Protein Degradation and Inhibitors 3
- Hematology 17
- Acute Myeloid Leukemia Research 10
- Multiple Myeloma Research and Treatments 7
- Co-authors
- Jeffrey M. Leiden (8 shared papers)Natarajan Muthusamy (3 shared papers)Chao-Nan Ting (2 shared papers)Min Lü (3 shared papers)Cynthia Clendenin (2 shared papers)Christopher Fischer (2 shared papers)Emily Barr (1 shared paper)Chay T. Kuo (1 shared paper)
- Journals
- Blood (6 papers)Neuro-Oncology (4 papers)British Journal of Haematology (3 papers)Nature (3 papers)BioEssays (2 papers)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Kevin Barton
47 papers receiving 3.2k citations
Kevin Barton's Hit Papers
Peers
Comparison fields: 5 of 100
- Immunology 1.0k
- Hematology 521
- Oncology 722
- Molecular Biology 1.8k
- Cancer Research 384
Countries citing papers authored by Kevin Barton
This map shows the geographic impact of Kevin Barton'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 Kevin Barton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Barton more than expected).
Fields of papers citing papers by Kevin Barton
This network shows the impact of papers produced by Kevin Barton. 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 Kevin Barton. The network helps show where Kevin Barton may publish in the future.
Co-authors
The 25 scholars most cited alongside Kevin Barton, 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 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Transcription factor GATA-3 is required for development of the T-cell lineage Hit paper breakdown → | 1996 | 516 |
| 2 | 1995 | 302 | |
| 3 | 1997 | 299 | |
| 4 | 1998 | 295 | |
| 5 | 1995 | 282 | |
| 6 | 1996 | 223 | |
| 7 | 2013 | 221 | |
| 8 | 2001 | 135 | |
| 9 | 2004 | 133 | |
| 10 | 2000 | 117 | |
| 11 | 2005 | 94 | |
| 12 | 2004 | 84 | |
| 13 | 1999 | 60 | |
| 14 | 2007 | 56 | |
| 15 | 2008 | 46 | |
| 16 | 2001 | 46 | |
| 17 | 2022 | 41 | |
| 18 | 2011 | 37 | |
| 19 | 2005 | 32 | |
| 20 | 1998 | 28 |
About Kevin Barton
Kevin Barton is a scholar working on Molecular Biology, Hematology, Genetics, Immunology and Oncology, having authored 50 papers that have together received 3.2k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (10 papers), Multiple Myeloma Research and Treatments (7 papers), Glioma Diagnosis and Treatment (7 papers), Immune Cell Function and Interaction (6 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), T-cell and B-cell Immunology (4 papers), Lymphoma Diagnosis and Treatment (4 papers) and Protein Degradation and Inhibitors (3 papers). The work is most often cited by research in Immunology (1.0k citations), Hematology (521 citations), Oncology (722 citations), Molecular Biology (1.8k citations) and Cancer Research (384 citations). Kevin Barton has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Jeffrey M. Leiden, Natarajan Muthusamy, Chao-Nan Ting, Min Lü, Cynthia Clendenin, Christopher Fischer, Emily Barr, Chay T. Kuo, Margaret Veselits and Serhan Alkan. Their work appears in journals such as Blood, Neuro-Oncology, British Journal of Haematology, Nature and BioEssays.
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.