Jay Mei
Impact in
- Hematology top 5%
- Multiple Myeloma Research and Treatments
- Genetics top 10%
- Chronic Lymphocytic Leukemia Research
Papers in
- Oncology 20
- CAR-T cell therapy research 7
- Cancer Treatment and Pharmacology 6
- Cancer Immunotherapy and Biomarkers 4
- Co-authors
- Steven P. Donald (4 shared papers)James M. Phang (4 shared papers)Jian Yu (1 shared paper)David Valle (1 shared paper)Norman G. Hord (2 shared papers)Dolores Winterstein (2 shared papers)Sui‐Po Zhang (1 shared paper)Na Qin (1 shared paper)
- Journals
- Blood (13 papers)Cancer Research (8 papers)Journal of Clinical Oncology (3 papers)Carcinogenesis (2 papers)Combinatorial Chemistry & High Throughput Screening (2 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Jay Mei
43 papers receiving 782 citations
Peers
Comparison fields: 5 of 89
- Hematology 204
- Genetics 110
- Cancer Research 139
- Oncology 236
- Biochemistry 55
Countries citing papers authored by Jay Mei
This map shows the geographic impact of Jay Mei'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 Jay Mei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Mei more than expected).
Fields of papers citing papers by Jay Mei
This network shows the impact of papers produced by Jay Mei. 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 Jay Mei. The network helps show where Jay Mei may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Mei, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Proline oxidase, encoded by p53-induced gene-6, catalyzes the generation of proline-dependent reactive oxygen species. | 2001 | 244 |
| 2 | 2005 | 60 | |
| 3 | 2002 | 50 | |
| 4 | 1999 | 47 | |
| 5 | 2013 | 39 | |
| 6 | 2013 | 38 | |
| 7 | 2000 | 38 | |
| 8 | 2010 | 38 | |
| 9 | 2009 | 30 | |
| 10 | 2013 | 28 | |
| 11 | 2006 | 27 | |
| 12 | 2011 | 22 | |
| 13 | 2016 | 15 | |
| 14 | 2024 | 11 | |
| 15 | 2016 | 11 | |
| 16 | 2005 | 11 | |
| 17 | 2017 | 11 | |
| 18 | 2004 | 10 | |
| 19 | 2004 | 8 | |
| 20 | 2015 | 7 |
About Jay Mei
Jay Mei is a scholar working on Oncology, Molecular Biology, Hematology, Genetics and Pulmonary and Respiratory Medicine, having authored 47 papers that have together received 808 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (9 papers), Multiple Myeloma Research and Treatments (9 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), CAR-T cell therapy research (7 papers), Cancer Treatment and Pharmacology (6 papers), Advanced Breast Cancer Therapies (6 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Lymphoma Diagnosis and Treatment (4 papers). The work is most often cited by research in Hematology (204 citations), Genetics (110 citations), Cancer Research (139 citations), Oncology (236 citations) and Biochemistry (55 citations). Jay Mei has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Steven P. Donald, James M. Phang, Jian Yu, David Valle, Norman G. Hord, Dolores Winterstein, Sui‐Po Zhang, Na Qin, Christopher M. Flores and Meletios Α. Dimopoulos. Their work appears in journals such as Blood, Cancer Research, Journal of Clinical Oncology, Carcinogenesis and Combinatorial Chemistry & High Throughput Screening.
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.