William J. Greenleaf

48.2k total citations · 13 hit papers
143 papers, 20.7k citations indexed

About

William J. Greenleaf is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, William J. Greenleaf has authored 143 papers receiving a total of 20.7k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Molecular Biology, 18 papers in Immunology and 15 papers in Cancer Research. Recurrent topics in William J. Greenleaf's work include Genomics and Chromatin Dynamics (43 papers), RNA and protein synthesis mechanisms (38 papers) and Single-cell and spatial transcriptomics (32 papers). William J. Greenleaf is often cited by papers focused on Genomics and Chromatin Dynamics (43 papers), RNA and protein synthesis mechanisms (38 papers) and Single-cell and spatial transcriptomics (32 papers). William J. Greenleaf collaborates with scholars based in United States, Sweden and Germany. William J. Greenleaf's co-authors include Howard Y. Chang, Jason D. Buenrostro, Beijing Wu, Paul G. Giresi, Lisa C. Zaba, Steven M. Block, Sandy Klemm, Zohar Shipony, M Snyder and Alicia N. Schep and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

William J. Greenleaf

135 papers receiving 20.5k citations

Hit Papers

Transposition of native chromatin for fast and sensit... 2005 2026 2012 2019 2013 2015 2015 2019 2017 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position
    2013 3.9k citations Jason D. Buenrostro, Howard Y. Chang et al. Nature Methods profile →
  2. ATAC‐seq: A Method for Assaying Chromatin Accessibility Genome‐Wide
    2015 2.0k citations Jason D. Buenrostro, Howard Y. Chang et al. profile →
  3. Single-cell chromatin accessibility reveals principles of regulatory variation
    2015 1.5k citations Jason D. Buenrostro, Howard Y. Chang et al. Nature profile →
  4. Chromatin accessibility and the regulatory epigenome
    2019 1.0k citations Sandy Klemm, William J. Greenleaf et al. profile →
  5. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data
    2017 770 citations Jason D. Buenrostro, William J. Greenleaf et al. Nature Methods profile →
  6. HiChIP: efficient and sensitive analysis of protein-directed genome architecture
    2016 685 citations Maxwell R. Mumbach, Adam J. Rubin et al. Nature Methods profile →
  7. Direct observation of base-pair stepping by RNA polymerase
    2005 657 citations William J. Greenleaf et al. Nature profile →
  8. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution
    2016 656 citations M. Ryan Corces, Jason D. Buenrostro et al. Nature Genetics profile →
  9. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis
    2021 561 citations Jeffrey M. Granja, M. Ryan Corces et al. Nature Genetics profile →
  10. Integrated Single-Cell Analysis Maps the Continuous Regulatory Landscape of Human Hematopoietic Differentiation
    2018 397 citations Jason D. Buenrostro, M. Ryan Corces et al. profile →
  11. Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution
    2021 219 citations Alexandro E. Trevino, Fabian Müller et al. profile →
  12. Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer
    2022 154 citations Anshul Kundaje, William J. Greenleaf et al. Nature Genetics profile →
  13. Short tandem repeats bind transcription factors to tune eukaryotic gene expression
    2023 98 citations Amr M. Alexandari, Michael G.B. Hayes et al. Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William J. Greenleaf United States 60 16.2k 2.8k 2.7k 2.5k 1.6k 143 20.7k
Heinrich Leonhardt Germany 74 17.7k 1.1× 1.5k 0.5× 985 0.4× 3.1k 1.2× 1.9k 1.2× 266 22.0k
John T. Lis United States 94 24.2k 1.5× 1.6k 0.6× 1.7k 0.6× 2.5k 1.0× 1.7k 1.1× 218 26.7k
Tom Misteli United States 86 23.5k 1.5× 2.5k 0.9× 1.9k 0.7× 2.5k 1.0× 1.6k 1.0× 196 28.5k
Alexander van Oudenaarden Netherlands 91 29.2k 1.8× 2.2k 0.8× 6.0k 2.2× 6.5k 2.6× 4.0k 2.5× 200 36.6k
Robert H. Singer United States 102 29.4k 1.8× 1.1k 0.4× 2.0k 0.7× 3.0k 1.2× 1.3k 0.8× 326 35.0k
Henning Urlaub Germany 83 20.3k 1.3× 1.6k 0.6× 2.4k 0.9× 1.8k 0.7× 1.3k 0.8× 445 24.9k
Edward H. Egelman United States 80 12.7k 0.8× 1.6k 0.6× 598 0.2× 3.5k 1.4× 791 0.5× 319 19.3k
Angus I. Lamond United Kingdom 93 24.9k 1.5× 1.7k 0.6× 2.1k 0.8× 2.3k 0.9× 2.2k 1.4× 268 28.7k
Michael K. Rosen United States 70 18.4k 1.1× 1.9k 0.7× 551 0.2× 1.4k 0.6× 903 0.6× 142 23.6k
Kaiqin Lao United States 30 8.4k 0.5× 848 0.3× 3.5k 1.3× 1.2k 0.5× 838 0.5× 48 10.7k

Countries citing papers authored by William J. Greenleaf

Since Specialization
Citations

This map shows the geographic impact of William J. Greenleaf'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 William J. Greenleaf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William J. Greenleaf more than expected).

Fields of papers citing papers by William J. Greenleaf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William J. Greenleaf. 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 William J. Greenleaf. The network helps show where William J. Greenleaf may publish in the future.

Co-authorship network of co-authors of William J. Greenleaf

This figure shows the co-authorship network connecting the top 25 collaborators of William J. Greenleaf. A scholar is included among the top collaborators of William J. Greenleaf 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 William J. Greenleaf. William J. Greenleaf 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.
Klemm, Sandy, et al.. (2025). Thymic epithelial cells amplify epigenetic noise to promote immune tolerance. Nature. 646(8085). 724–733. 1 indexed citations
2.
Favaro, Patrícia, David R. Glass, Albert G. Tsai, et al.. (2024). Terminal deoxynucleotidyl transferase and CD84 identify human multi-potent lymphoid progenitors. Nature Communications. 15(1). 5910–5910.
3.
Parks, Benjamin, et al.. (2024). PU.1 and BCL11B sequentially cooperate with RUNX1 to anchor mSWI/SNF to poise the T cell effector landscape. Nature Immunology. 25(5). 860–872. 12 indexed citations
4.
Limouse, Charles, et al.. (2023). Global mapping of RNA-chromatin contacts reveals a proximity-dominated connectivity model for ncRNA-gene interactions. Nature Communications. 14(1). 6073–6073. 10 indexed citations
5.
Alexandari, Amr M., Michael G.B. Hayes, Emil Marklund, et al.. (2023). Short tandem repeats bind transcription factors to tune eukaryotic gene expression. Science. 381(6664). eadd1250–eadd1250. 98 indexed citations breakdown →
6.
Mello, Stephano S., Paweł K. Mazur, James J. Lee, et al.. (2023). Multifaceted role for p53 in pancreatic cancer suppression. Proceedings of the National Academy of Sciences. 120(10). e2211937120–e2211937120. 22 indexed citations
7.
Shin, John H., Steve Bonilla, Sarah K. Denny, William J. Greenleaf, & Daniel Herschlag. (2023). Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements. Proceedings of the National Academy of Sciences. 120(11). e2220485120–e2220485120. 3 indexed citations
8.
Ober‐Reynolds, Benjamin, Chen Wang, Justin Ko, et al.. (2023). Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases. Nature Genetics. 55(8). 1288–1300. 27 indexed citations
9.
Pierce, Sarah E., Jeffrey M. Granja, M. Ryan Corces, et al.. (2021). LKB1 inactivation modulates chromatin accessibility to drive metastatic progression. Nature Cell Biology. 23(8). 915–924. 34 indexed citations
10.
Gennert, David, Rachel C. Lynn, Evan Weber, et al.. (2021). Dynamic chromatin regulatory landscape of human CAR T cell exhaustion. Proceedings of the National Academy of Sciences. 118(30). 45 indexed citations
11.
Trevino, Alexandro E., Nasa Sinnott-Armstrong, Jimena Andersen, et al.. (2020). Chromatin accessibility dynamics in a model of human forebrain development. Science. 367(6476). 149 indexed citations
12.
Jadhav, Rohit R., Se Jin Im, Bin Hu, et al.. (2019). Epigenetic signature of PD-1+ TCF1+ CD8 T cells that act as resource cells during chronic viral infection and respond to PD-1 blockade. Proceedings of the National Academy of Sciences. 116(28). 14113–14118. 154 indexed citations
13.
Kappel, Kalli, Inga Jarmoskaite, Pavanapuresan P. Vaidyanathan, et al.. (2019). Blind tests of RNA–protein binding affinity prediction. Proceedings of the National Academy of Sciences. 116(17). 8336–8341. 18 indexed citations
14.
Mumbach, Maxwell R., Jeffrey M. Granja, Ryan A. Flynn, et al.. (2019). HiChIRP reveals RNA-associated chromosome conformation. Nature Methods. 16(6). 489–492. 64 indexed citations
15.
Yang, Dian, Sarah K. Denny, Peyton Greenside, et al.. (2018). Intertumoral Heterogeneity in SCLC Is Influenced by the Cell Type of Origin. Cancer Discovery. 8(10). 1316–1331. 104 indexed citations
16.
Boyle, Evan A., Johan O. L. Andreasson, Lauren Chircus, et al.. (2017). High-throughput biochemical profiling reveals sequence determinants of dCas9 off-target binding and unbinding. Proceedings of the National Academy of Sciences. 114(21). 5461–5466. 143 indexed citations
17.
Miller, Erik L., Diana C. Hargreaves, Cigall Kadoch, et al.. (2017). TOP2 synergizes with BAF chromatin remodeling for both resolution and formation of facultative heterochromatin. Nature Structural & Molecular Biology. 24(4). 344–352. 64 indexed citations
18.
Wang, Jinpeng, Jingwen Yu, Qin Yang, et al.. (2016). Multiparameter Particle Display (MPPD): A Quantitative Screening Method for the Discovery of Highly Specific Aptamers. Angewandte Chemie. 129(3). 762–765. 9 indexed citations
19.
Wang, Jinpeng, Jingwen Yu, Qin Yang, et al.. (2016). Multiparameter Particle Display (MPPD): A Quantitative Screening Method for the Discovery of Highly Specific Aptamers. Angewandte Chemie International Edition. 56(3). 744–747. 73 indexed citations
20.
Morris, Richard B., William J. Greenleaf, & Robert H. Ferrell. (1971). America: a history of the people. 1 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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