Jay L. Hess
- Hematology top 0.2%
- Acute Myeloid Leukemia Research 52
- Chronic Myeloid Leukemia Treatments 9
- Molecular Biology top 0.5%
- Genomics and Chromatin Dynamics 31
- Epigenetics and DNA Methylation 25
- Cancer-related gene regulation 19
- Protein Degradation and Inhibitors 17
- Ubiquitin and proteasome pathways 10
- Virology top 2%
- Genetics top 1%
- Chronic Lymphocytic Leukemia Research 11
- Oncology top 2%
- Co-authors
- Thomas A. MilneAndrew G. MunteanStanley J. KorsmeyerBenjamin YuHugh W. BrockMary Ellen MartinC. David AllisRobert K. Slany
- Cited by
- HematologyMolecular BiologyVirology
- Journals
- Blood (23 papers)Archives of Pathology & Laboratory Medicine (8 papers)Proceedings of the National Academy of Sciences (8 papers)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Jay L. Hess
119 papers receiving 9.7k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Hematology 3.2k
- Molecular Biology 7.4k
- Virology 324
- Genetics 615
- Oncology 1.1k
Countries citing papers authored by Jay L. Hess
This map shows the geographic impact of Jay L. Hess'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 L. Hess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay L. Hess more than expected).
Fields of papers citing papers by Jay L. Hess
This network shows the impact of papers produced by Jay L. Hess. 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 L. Hess. The network helps show where Jay L. Hess may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jay L. Hess, 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 | 2025 | 1 | |
| 2 | 2019 | 4 | |
| 3 | 2018 | 86 | |
| 4 | Deregulation of the HOXA9/MEIS1 Axis in Acute Leukemia | 2016 | 2 |
| 5 | C/EBPα is an essential collaborator in Hoxa9/Meis1-mediated leukemogenesis | 2014 | 1 |
| 6 | 2012 | 30 | |
| 7 | 2010 | 179 | |
| 8 | 2009 | 67 | |
| 9 | 2007 | 164 | |
| 10 | 2006 | 139 | |
| 11 | 2005 | 141 | |
| 12 | MLL Targets SET Domain Methyltransferase Activity to Hox Gene Promotersbreakdown → | 2002 | 833 |
| 13 | 2002 | 7 | |
| 14 | 2001 | 36 | |
| 15 | 2000 | 2 | |
| 16 | 1999 | 44 | |
| 17 | 1997 | 37 | |
| 18 | 1996 | 3 | |
| 19 | 1996 | 19 | |
| 20 | 1993 | 76 |
About Jay L. Hess
Jay L. Hess is a scholar working on Hematology, Genetics and Molecular Biology, having authored 120 papers that have together received 9.9k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (52 papers), Genomics and Chromatin Dynamics (31 papers), Epigenetics and DNA Methylation (25 papers), Cancer-related gene regulation (19 papers), Protein Degradation and Inhibitors (17 papers), Chronic Lymphocytic Leukemia Research (11 papers), Ubiquitin and proteasome pathways (10 papers) and Chronic Myeloid Leukemia Treatments (9 papers). The work is most often cited by research in Hematology (3.2k citations), Molecular Biology (7.4k citations) and Virology (324 citations). Jay L. Hess has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Thomas A. Milne, Andrew G. Muntean, Stanley J. Korsmeyer, Benjamin Yu, Hugh W. Brock, Mary Ellen Martin, C. David Allis, Robert K. Slany, Yali Dou and Denise Gibbs. Their work appears in journals such as Blood, Archives of Pathology & Laboratory Medicine, Proceedings of the National Academy of Sciences, Journal of Virology and Molecular and Cellular Biology.
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.