Chad May
Impact in
- Genetics top 2%
- Virus-based gene therapy research
- Hemoglobinopathies and Related Disorders
- Hematology top 2%
- Hematopoietic Stem Cell Transplantation
Papers in
-
- CRISPR and Genetic Engineering 8
- Angiogenesis and VEGF in Cancer 4
- Oncology 13
- CAR-T cell therapy research 8
- Co-authors
- Michel Sadelain (11 shared papers)Stefano Rivella (7 shared papers)J Callegari (3 shared papers)Glenn Heller (3 shared papers)Amy Chadburn (2 shared papers)Lucio Luzzatto (1 shared paper)K M Gaensler (1 shared paper)Hans‐Peter Gerber (3 shared papers)
- Journals
- Blood (5 papers)Journal of Pharmacology and Experimental Therapeutics (2 papers)Journal of Virology (2 papers)Biochemical Pharmacology (2 papers)JNCI Journal of the National Cancer Institute (1 paper)
- Partner nations
- United StatesFranceGermany
In The Last Decade
Chad May
35 papers receiving 2.6k citations
Chad May's Hit Papers
Peers
Comparison fields: 5 of 98
- Genetics 568
- Hematology 541
- Genetics 791
- Oncology 679
- Molecular Biology 1.4k
Countries citing papers authored by Chad May
This map shows the geographic impact of Chad May'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 Chad May with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chad May more than expected).
Fields of papers citing papers by Chad May
This network shows the impact of papers produced by Chad May. 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 Chad May. The network helps show where Chad May may publish in the future.
Co-authors
The 25 scholars most cited alongside Chad May, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Endothelial Cells Are Essential for the Self-Renewal and Repopulation of Notch-Dependent Hematopoietic Stem Cells Hit paper breakdown → | 2010 | 488 |
| 2 | 2000 | 446 | |
| 3 | 2003 | 179 | |
| 4 | 2003 | 173 | |
| 5 | 2000 | 167 | |
| 6 | 2015 | 141 | |
| 7 | 2002 | 132 | |
| 8 | 2010 | 123 | |
| 9 | 2020 | 113 | |
| 10 | 2005 | 80 | |
| 11 | 2005 | 78 | |
| 12 | 2000 | 76 | |
| 13 | 2012 | 61 | |
| 14 | 2002 | 56 | |
| 15 | 1995 | 54 | |
| 16 | 2010 | 48 | |
| 17 | 2007 | 44 | |
| 18 | 2020 | 41 | |
| 19 | Limited proliferation and telomere dysfunction following telomerase inhibition in immortal murine fibroblasts. | 2002 | 37 |
| 20 | 2017 | 31 |
About Chad May
Chad May is a scholar working on Molecular Biology, Oncology, Genetics, Radiology, Nuclear Medicine and Imaging and Immunology, having authored 35 papers that have together received 2.7k indexed citations. Recurring topics across this work include Virus-based gene therapy research (11 papers), CAR-T cell therapy research (8 papers), CRISPR and Genetic Engineering (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Acute Lymphoblastic Leukemia research (5 papers), Angiogenesis and VEGF in Cancer (4 papers), Hematopoietic Stem Cell Transplantation (3 papers) and Telomeres, Telomerase, and Senescence (3 papers). The work is most often cited by research in Genetics (568 citations), Hematology (541 citations), Genetics (791 citations), Oncology (679 citations) and Molecular Biology (1.4k citations). Chad May has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Michel Sadelain, Stefano Rivella, J Callegari, Glenn Heller, Amy Chadburn, Lucio Luzzatto, K M Gaensler, Hans‐Peter Gerber, Puja Sapra and Isabelle Rivière. Their work appears in journals such as Blood, Journal of Pharmacology and Experimental Therapeutics, Journal of Virology, Biochemical Pharmacology and JNCI Journal of the National Cancer Institute.
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.