Charles B. Epstein

27.8k total citations · 1 hit paper
57 papers, 6.3k citations indexed

About

Charles B. Epstein is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Charles B. Epstein has authored 57 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 12 papers in Oncology and 10 papers in Hematology. Recurrent topics in Charles B. Epstein's work include Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (7 papers) and Gene expression and cancer classification (6 papers). Charles B. Epstein is often cited by papers focused on Genomics and Chromatin Dynamics (10 papers), Epigenetics and DNA Methylation (7 papers) and Gene expression and cancer classification (6 papers). Charles B. Epstein collaborates with scholars based in United States, Germany and Taiwan. Charles B. Epstein's co-authors include B Bernstein, Frederick R. Cross, Noam Shoresh, Michael J. Coyne, Xiaolan Zhang, Timothy Durham, Robbyn Issner, Manolis Kellis, Jason Ernst and Tarjei S. Mikkelsen and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Charles B. Epstein

55 papers receiving 6.1k citations

Hit Papers

Mapping and analysis of chromatin state dynamics in nine ... 2011 2026 2016 2021 2011 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Charles B. Epstein United States 31 4.7k 925 618 515 439 57 6.3k
Tim Thomas Australia 46 4.4k 0.9× 931 1.0× 424 0.7× 588 1.1× 670 1.5× 138 6.3k
Kirby D. Smith United States 39 4.6k 1.0× 1.5k 1.6× 403 0.7× 355 0.7× 784 1.8× 93 6.3k
Eric Lieberman Greer United States 28 6.4k 1.4× 586 0.6× 448 0.7× 955 1.9× 342 0.8× 43 8.7k
Naomi Nakagata Japan 46 3.6k 0.8× 1.7k 1.9× 450 0.7× 437 0.8× 161 0.4× 236 7.4k
Claude Szpirer Belgium 39 3.0k 0.6× 1.8k 1.9× 420 0.7× 362 0.7× 286 0.7× 190 5.3k
Jacques Samarut France 58 5.3k 1.1× 2.4k 2.6× 1.0k 1.7× 777 1.5× 198 0.5× 180 9.5k
David M. Kurnit United States 37 4.7k 1.0× 1.5k 1.6× 690 1.1× 578 1.1× 529 1.2× 116 8.0k
Moshe Shani Israel 39 4.3k 0.9× 1.4k 1.5× 613 1.0× 514 1.0× 211 0.5× 99 6.6k
Victor Guryev Netherlands 36 3.9k 0.8× 1.6k 1.7× 653 1.1× 989 1.9× 646 1.5× 124 5.9k
Yun Huang United States 45 6.4k 1.4× 950 1.0× 540 0.9× 816 1.6× 302 0.7× 152 8.4k

Countries citing papers authored by Charles B. Epstein

Since Specialization
Citations

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

Fields of papers citing papers by Charles B. Epstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles B. Epstein. 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 Charles B. Epstein. The network helps show where Charles B. Epstein may publish in the future.

Co-authorship network of co-authors of Charles B. Epstein

This figure shows the co-authorship network connecting the top 25 collaborators of Charles B. Epstein. A scholar is included among the top collaborators of Charles B. Epstein 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 Charles B. Epstein. Charles B. Epstein 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.
Issner, Robbyn, Nauman Javed, Jason D. Buenrostro, et al.. (2025). Multi-locus CRISPRi targeting with a single truncated guide RNA. Nature Communications. 16(1). 1357–1357. 1 indexed citations
2.
Talluri, Srikanth, Moritz Binder, Eugenio Morelli, et al.. (2025). Loss of BCL7A permits IRF4 transcriptional activity and cellular growth in multiple myeloma. Blood. 146(1). 104–114. 1 indexed citations
3.
Jung, Youngsook L., Wenping Zhao, Dhawal Jain, et al.. (2024). Epigenetic profiling reveals key genes and cis-regulatory networks specific to human parathyroids. Nature Communications. 15(1). 2106–2106. 2 indexed citations
4.
Sumida, Tomokazu S., Matthew R. Lincoln, Liang He, et al.. (2024). An autoimmune transcriptional circuit drives FOXP3 + regulatory T cell dysfunction. Science Translational Medicine. 16(762). eadp1720–eadp1720. 8 indexed citations
5.
Yao, Yao, Mehmet Samur, Eugenio Morelli, et al.. (2023). CDK7 controls E2F- and MYC-driven proliferative and metabolic vulnerabilities in multiple myeloma. Blood. 141(23). 2841–2852. 17 indexed citations
6.
Yao, Qiuming, Charles B. Epstein, Robbyn Issner, et al.. (2020). Epigenetic Alterations in Keratinocyte Carcinoma. Journal of Investigative Dermatology. 141(5). 1207–1218. 8 indexed citations
7.
Javed, Nauman, Yossi Farjoun, Tim Fennell, et al.. (2020). Detecting sample swaps in diverse NGS data types using linkage disequilibrium. Nature Communications. 11(1). 3697–3697. 13 indexed citations
8.
Ryan, Russell J.H., Yotam Drier, Holly Whitton, et al.. (2015). Detection of Enhancer-Associated Rearrangements Reveals Mechanisms of Oncogene Dysregulation in B-cell Lymphoma. Cancer Discovery. 5(10). 1058–1071. 86 indexed citations
9.
Zhu, Jiang, Mazhar Adli, James Zou, et al.. (2013). Genome-wide Chromatin State Transitions Associated with Developmental and Environmental Cues. Cell. 152(3). 642–654. 380 indexed citations
10.
Zullo, Joseph, Ignacio A. Demarco, Roger Piqué-Regi, et al.. (2012). DNA Sequence-Dependent Compartmentalization and Silencing of Chromatin at the Nuclear Lamina. Cell. 149(7). 1474–1487. 342 indexed citations
11.
Ram, Oren, Alon Goren, Ido Amit, et al.. (2011). Combinatorial Patterning of Chromatin Regulators Uncovered by Genome-wide Location Analysis in Human Cells. Cell. 147(7). 1628–1639. 250 indexed citations
12.
Jin, Can, Antoni Barrientos, Charles B. Epstein, Ronald A. Butow, & Alexander Tzagoloff. (2007). SIT4 regulation of Mig1p‐mediated catabolite repression in Saccharomyces cerevisiae. FEBS Letters. 581(29). 5658–5663. 15 indexed citations
13.
Epstein, Charles B., Hong Liu, Nanxiang Ge, et al.. (2004). Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study. BMC Genomics. 5(1). 26–26. 72 indexed citations
14.
McCammon, Mark T., Charles B. Epstein, Beata Przybyla‐Zawislak, Lee McAlister-Henn, & Ronald A. Butow. (2003). Global Transcription Analysis of Krebs Tricarboxylic Acid Cycle Mutants Reveals an Alternating Pattern of Gene Expression and Effects on Hypoxic and Oxidative Genes. Molecular Biology of the Cell. 14(3). 958–972. 85 indexed citations
15.
Epstein, Charles B., Walker Hale, & Ronald A. Butow. (2001). Numerical methods for handling uncertainty in microarray data: An example analyzing perturbed mitochondrial function in yeast. Methods in cell biology. 65. 439–495. 17 indexed citations
16.
Epstein, Charles B.. (2000). Microarray technology — enhanced versatility, persistent challenge. Current Opinion in Biotechnology. 11(1). 36–41. 94 indexed citations
18.
Ladenheim, Bruce, Hiroshi Hirata, Richard B. Rothman, et al.. (1995). Superoxide radicals mediate the biochemical effects of methylenedioxymethamphetamine (MDMA): Evidence from using CuZn‐superoxide dismutase transgenic mice. Synapse. 21(2). 169–176. 65 indexed citations
20.
Preisler, Harvey D., et al.. (1979). Growth of human acute myeloblastic leukemic (AML) cells in vitro. Annals of Hematology. 38(1). 35–45. 3 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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