Payel Sen

4.4k total citations · 1 hit paper
47 papers, 2.0k citations indexed

About

Payel Sen is a scholar working on Molecular Biology, Physiology and Aging. According to data from OpenAlex, Payel Sen has authored 47 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 11 papers in Physiology and 8 papers in Aging. Recurrent topics in Payel Sen's work include Genomics and Chromatin Dynamics (15 papers), Telomeres, Telomerase, and Senescence (9 papers) and Genetics, Aging, and Longevity in Model Organisms (8 papers). Payel Sen is often cited by papers focused on Genomics and Chromatin Dynamics (15 papers), Telomeres, Telomerase, and Senescence (9 papers) and Genetics, Aging, and Longevity in Model Organisms (8 papers). Payel Sen collaborates with scholars based in United States, Germany and United Kingdom. Payel Sen's co-authors include Shelley L. Berger, Parisha P. Shah, Raffaella Nativio, Blaine Bartholomew, Na Yang, Greg Donahue, Abhijit Shukla, Sukesh R. Bhaumik, Peter D. Adams and Zhixun Dou and has published in prestigious journals such as Cell, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Payel Sen

46 papers receiving 2.0k citations

Hit Papers

Epigenetic Mechanisms of Longevity and Aging 2016 2026 2019 2022 2016 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Payel Sen United States 22 1.5k 407 240 232 223 47 2.0k
Lucy G. Andrews United States 23 1.9k 1.3× 712 1.7× 218 0.9× 115 0.5× 169 0.8× 41 2.6k
Ying Hong United Kingdom 22 1.1k 0.7× 810 2.0× 230 1.0× 152 0.7× 585 2.6× 57 2.5k
Francesca Rossiello Italy 11 884 0.6× 953 2.3× 137 0.6× 296 1.3× 225 1.0× 16 1.6k
Gijs van Haaften Netherlands 29 1.8k 1.2× 178 0.4× 230 1.0× 324 1.4× 71 0.3× 62 2.6k
Xiaoping Zhu China 17 857 0.6× 124 0.3× 134 0.6× 147 0.6× 102 0.5× 28 1.4k
Agustina D’Urso United States 12 1.2k 0.8× 378 0.9× 229 1.0× 59 0.3× 122 0.5× 13 2.0k
Michael Van Meter United States 12 1.1k 0.7× 430 1.1× 129 0.5× 147 0.6× 180 0.8× 18 1.9k
Jozef Madžo United States 20 1.0k 0.7× 141 0.3× 201 0.8× 53 0.2× 149 0.7× 52 1.5k
George B. John United States 15 1.6k 1.0× 187 0.5× 138 0.6× 55 0.2× 123 0.6× 20 2.6k
Nicholas Schaum United States 8 659 0.4× 469 1.2× 184 0.8× 152 0.7× 244 1.1× 10 1.3k

Countries citing papers authored by Payel Sen

Since Specialization
Citations

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

Fields of papers citing papers by Payel Sen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Payel Sen. 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 Payel Sen. The network helps show where Payel Sen may publish in the future.

Co-authorship network of co-authors of Payel Sen

This figure shows the co-authorship network connecting the top 25 collaborators of Payel Sen. A scholar is included among the top collaborators of Payel Sen 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 Payel Sen. Payel Sen 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.
Sun, Zhengwu, et al.. (2025). Optimized Conditions for Electrical Tissue Stimulation with Biphasic, Charge-Balanced Impulses. Bioengineering. 12(3). 234–234. 1 indexed citations
2.
Mazucanti, Caio Henrique, Jennifer O’Connell, Dimitrios Tsitsipatis, et al.. (2025). Pig Taste Cell-derived Organoids Synthesize Insulin. Endocrinology. 166(9). 1 indexed citations
3.
Herzog, Chiara, Jesse R. Poganik, Nir Barzilai, et al.. (2025). Biomarkers of Aging– NIA Joint Symposium 2024: New Insights Into Aging Biomarkers. Aging Cell. 24(7). e70124–e70124.
4.
Sen, Payel, et al.. (2024). Retinoic acid modulation guides human-induced pluripotent stem cell differentiation towards left or right ventricle-like cardiomyocytes. Stem Cell Research & Therapy. 15(1). 184–184. 2 indexed citations
5.
Sen, Payel, et al.. (2024). Linking Aging to Cancer: The Role of Chromatin Biology. The Journals of Gerontology Series A. 79(7). 1 indexed citations
6.
Sen, Payel & Priyatansh Gurha. (2023). Understanding cardiac senescence one cell type at a time. PubMed. 3(2). 1 indexed citations
7.
Saha, Dhurjhoti, Arjan Hada, Junwoo Lee, et al.. (2023). The AT-hook is an evolutionarily conserved auto-regulatory domain of SWI/SNF required for cell lineage priming. Nature Communications. 14(1). 4682–4682. 4 indexed citations
8.
Sen, Payel, Greg Donahue, Gabor Egervári, et al.. (2023). Spurious intragenic transcription is a feature of mammalian cellular senescence and tissue aging. Nature Aging. 3(4). 402–417. 17 indexed citations
9.
Dijk, Chris Van, Payel Sen, Oana Sorop, et al.. (2023). Impaired cardiac BCAA catabolism associated with impaired myocardial efficiency during exercise in a porcine model with multiple risk factors. European Heart Journal. 44(Supplement_2). 1 indexed citations
10.
Egervári, Gabor, Simone Sidoli, Greg Donahue, et al.. (2022). Enzymatic transfer of acetate on histones from lysine reservoir sites to lysine activating sites. Science Advances. 8(3). eabj5688–eabj5688. 39 indexed citations
11.
Dittrich‐Breiholz, Oliver, Hermann Haller, Payel Sen, et al.. (2022). Single cell versus single nucleus: transcriptome differences in the murine kidney after ischemia-reperfusion injury. American Journal of Physiology-Renal Physiology. 323(2). F171–F181. 12 indexed citations
12.
Anthonymuthu, Tamil S., Himaly Shinglot, Payel Sen, et al.. (2022). Integrated -omics approach reveals persistent DNA damage rewires lipid metabolism and histone hyperacetylation via MYS-1/Tip60. Science Advances. 8(7). eabl6083–eabl6083. 16 indexed citations
13.
Tsitsipatis, Dimitrios, Yulan Piao, Marc Michel, et al.. (2022). Improved Macrophage Enrichment from Mouse Skeletal Muscle. BIO-PROTOCOL. 12(23). 4 indexed citations
14.
Cui, Chang‐Yi, Krystyna Mazan-Mamczarz, Christopher Dunn, et al.. (2022). Single-cell analysis of skeletal muscle macrophages reveals age-associated functional subpopulations. eLife. 11. 64 indexed citations
15.
Herman, Allison B., Carlos Anerillas, Rachel Munk, et al.. (2021). Reduction of lamin B receptor levels by miR-340-5p disrupts chromatin, promotes cell senescence and enhances senolysis. Nucleic Acids Research. 49(13). 7389–7405. 18 indexed citations
16.
Herman, Allison B., et al.. (2021). Epigenetic dysregulation in cardiovascular aging and disease. PubMed. 1. 28 indexed citations
17.
Sen, Payel. (2020). High-throughput chromatin screens to identify targets of senescence and aging. SHILAP Revista de lepidopterología. 4. 73–75. 1 indexed citations
18.
Sen, Payel, Yemin Lan, Simone Sidoli, et al.. (2019). Histone Acetyltransferase p300 Induces De Novo Super-Enhancers to Drive Cellular Senescence. Molecular Cell. 73(4). 684–698.e8. 106 indexed citations
19.
Sen, Payel, Sujana Ghosh, B. Franklin Pugh, & Blaine Bartholomew. (2011). A new, highly conserved domain in Swi2/Snf2 is required for SWI/SNF remodeling. Nucleic Acids Research. 39(21). 9155–9166. 40 indexed citations
20.
Malik, Shivani, Abhijit Shukla, Payel Sen, & Sukesh R. Bhaumik. (2009). The 19 S Proteasome Subcomplex Establishes a Specific Protein Interaction Network at the Promoter for Stimulated Transcriptional Initiation in Vivo. Journal of Biological Chemistry. 284(51). 35714–35724. 35 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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