Jay L. Hess

13.7k total citations · 4 hit papers
120 papers, 9.9k citations indexed

About

Jay L. Hess is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Jay L. Hess has authored 120 papers receiving a total of 9.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 57 papers in Hematology and 14 papers in Genetics. Recurrent topics in Jay L. Hess's work include Acute Myeloid Leukemia Research (52 papers), Genomics and Chromatin Dynamics (31 papers) and Epigenetics and DNA Methylation (25 papers). Jay L. Hess is often cited by papers focused on Acute Myeloid Leukemia Research (52 papers), Genomics and Chromatin Dynamics (31 papers) and Epigenetics and DNA Methylation (25 papers). Jay L. Hess collaborates with scholars based in United States, Germany and Canada. Jay L. Hess's co-authors include Thomas A. Milne, Andrew G. Muntean, Stanley J. Korsmeyer, Benjamin Yu, Hugh W. Brock, Mary Ellen Martin, C. David Allis, Yali Dou, Robert K. Slany and Denise Gibbs and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Jay L. Hess

119 papers receiving 9.7k citations

Hit Papers

MLL Targets SET Domain Methyltransferase Activity to Hox ... 1995 2026 2005 2015 2002 1995 2005 2004 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay L. Hess United States 50 7.4k 3.2k 1.1k 988 825 120 9.9k
Bryan D. Young United Kingdom 61 5.2k 0.7× 1.9k 0.6× 1.6k 1.4× 477 0.5× 1.5k 1.8× 191 9.2k
Anna Jauch Germany 43 5.2k 0.7× 1.8k 0.6× 1.6k 1.4× 445 0.5× 1.6k 2.0× 194 7.7k
Manuel O. Dı́az United States 47 4.3k 0.6× 1.6k 0.5× 1.5k 1.3× 308 0.3× 991 1.2× 108 7.4k
Stuart H. Orkin United States 38 5.5k 0.7× 1.5k 0.5× 918 0.8× 389 0.4× 909 1.1× 62 8.4k
Toshiya Inaba Japan 37 2.6k 0.4× 1.7k 0.5× 799 0.7× 289 0.3× 443 0.5× 124 4.6k
Rolf Marschalek Germany 40 3.3k 0.5× 2.0k 0.6× 569 0.5× 361 0.4× 397 0.5× 225 5.4k
Issay Kitabayashi Japan 41 4.4k 0.6× 1.5k 0.5× 1.1k 1.0× 373 0.4× 557 0.7× 121 6.1k
Kojo S.J. Elenitoba‐Johnson United States 47 3.7k 0.5× 876 0.3× 2.0k 1.7× 698 0.7× 528 0.6× 190 7.9k
C M Croce United States 46 5.2k 0.7× 1.3k 0.4× 2.4k 2.1× 303 0.3× 1.4k 1.7× 102 8.8k
Takuro Nakamura Japan 42 3.9k 0.5× 1.1k 0.3× 1.9k 1.7× 302 0.3× 606 0.7× 214 7.1k

Countries citing papers authored by Jay L. Hess

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Jay L. Hess

This figure shows the co-authorship network connecting the top 25 collaborators of Jay L. Hess. A scholar is included among the top collaborators of Jay L. Hess based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay L. Hess. Jay L. Hess is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Peng, Lei, Hong Guo-Parke, Peilin Ma, et al.. (2019). HoxA9 binds and represses the Cebpa +8 kb enhancer. PLoS ONE. 14(5). e0217604–e0217604. 4 indexed citations
2.
Collins, Cailin & Jay L. Hess. (2016). Deregulation of the HOXA9/MEIS1 Axis in Acute Leukemia. PMC. 2 indexed citations
3.
Collins, Cailin, Jingya Wang, Hongzhi Miao, et al.. (2014). C/EBPα is an essential collaborator in Hoxa9/Meis1-mediated leukemogenesis. PMC. 1 indexed citations
4.
Grembecka, Jolanta, Shihan He, Aibin Shi, et al.. (2012). Menin-MLL inhibitors reverse oncogenic activity of MLL fusion proteins in leukemia. Nature Chemical Biology. 8(3). 277–284. 325 indexed citations
5.
Maillard, Ivan, et al.. (2011). Requirement for Dot1l in murine postnatal hematopoiesis and leukemogenesis by MLL translocation. Blood. 117(18). 4759–4768. 150 indexed citations
6.
Muntean, Andrew G., Jiaying Tan, Kajal Sitwala, et al.. (2010). The PAF Complex Synergizes with MLL Fusion Proteins at HOX Loci to Promote Leukemogenesis. Cancer Cell. 17(6). 609–621. 179 indexed citations
7.
Milne, Thomas A., Keji Zhao, & Jay L. Hess. (2009). Chromatin Immunoprecipitation (ChIP) for Analysis of Histone Modifications and Chromatin-Associated Proteins. Methods in molecular biology. 538. 409–423. 62 indexed citations
8.
Muntean, Andrew G. & Jay L. Hess. (2009). Epigenetic Dysregulation in Cancer. American Journal Of Pathology. 175(4). 1353–1361. 58 indexed citations
9.
Fisher, Cynthia L., Sébastien Bloyer, Andreas Dahl, et al.. (2009). Additional sex combs-like 1 belongs to the enhancer of trithorax and polycomb group and genetically interacts with Cbx2 in mice. Developmental Biology. 337(1). 9–15. 67 indexed citations
10.
Caslini, Corrado, et al.. (2007). Interaction of MLL Amino Terminal Sequences with Menin Is Required for Transformation. Cancer Research. 67(15). 7275–7283. 164 indexed citations
11.
Yan, Jizhou, Karen Keeshan, Anthony Tubbs, et al.. (2006). The tumor suppressor menin regulates hematopoiesis and myeloid transformation by influencing Hox gene expression. Proceedings of the National Academy of Sciences. 103(4). 1018–1023. 139 indexed citations
12.
Hess, Jay L., et al.. (2006). MLL Core Components Give the Green Light to Histone Methylation. ACS Chemical Biology. 1(8). 495–498. 36 indexed citations
13.
Milne, Thomas A., Mary Ellen Martin, Hugh W. Brock, Robert K. Slany, & Jay L. Hess. (2005). Leukemogenic MLL Fusion Proteins Bind across a Broad Region of the Hox a9 Locus, Promoting Transcription and Multiple Histone Modifications. Cancer Research. 65(24). 11367–11374. 141 indexed citations
14.
Mitra‐Kaushik, Shibani, John C. S. Harding, Jay L. Hess, Robert D. Schreiber, & Lee Ratner. (2004). Enhanced tumorigenesis in HTLV-1 Tax-transgenic mice deficient in interferon-gamma. Blood. 104(10). 3305–3311. 47 indexed citations
15.
Hess, Jay L.. (2004). MLL: a histone methyltransferase disrupted in leukemia. Trends in Molecular Medicine. 10(10). 500–507. 263 indexed citations
16.
Milne, Thomas A., Scott Briggs, Hugh W. Brock, et al.. (2002). MLL Targets SET Domain Methyltransferase Activity to Hox Gene Promoters. Molecular Cell. 10(5). 1107–1117. 833 indexed citations breakdown →
17.
Khariwala, Samir S., et al.. (2000). Quiz case 2. Natural killer (NK) cell/peripheral T-cell lymphoma.. PubMed. 126(11). 1391, 1393–1391, 1393. 6 indexed citations
18.
Kaleem, Zahid, et al.. (1999). Acute Promyelocytic Leukemia With Additional Chromosomal Abnormalities and Absence of Auer Rods. American Journal of Clinical Pathology. 112(1). 113–118. 9 indexed citations
19.
Naughton, Michael, Jay L. Hess, Mary M. Zutter, & Nancy L. Bartlett. (1998). Bone marrow staging in patients with non-hodgkin's lymphoma. Cancer. 82(6). 1154–1159. 35 indexed citations
20.
Shivdasani, Ramesh A., et al.. (1993). Intermediate lymphocytic lymphoma: clinical and pathologic features of a recently characterized subtype of non-Hodgkin's lymphoma.. Journal of Clinical Oncology. 11(4). 802–111. 76 indexed citations

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.

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