Isabel Beerman

5.2k total citations · 2 hit papers
45 papers, 3.1k citations indexed

About

Isabel Beerman is a scholar working on Molecular Biology, Hematology and Immunology. According to data from OpenAlex, Isabel Beerman has authored 45 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 18 papers in Hematology and 14 papers in Immunology. Recurrent topics in Isabel Beerman's work include Hematopoietic Stem Cell Transplantation (16 papers), Epigenetics and DNA Methylation (12 papers) and Acute Myeloid Leukemia Research (8 papers). Isabel Beerman is often cited by papers focused on Hematopoietic Stem Cell Transplantation (16 papers), Epigenetics and DNA Methylation (12 papers) and Acute Myeloid Leukemia Research (8 papers). Isabel Beerman collaborates with scholars based in United States, United Kingdom and Sweden. Isabel Beerman's co-authors include Derrick J. Rossi, Irving L. Weissman, William J. Maloney, Elizabeth Price, Debashis Sahoo, Stanley L. Schrier, Wendy W. Pang, Hongcang Gu, Alexander Meissner and Zachary D. Smith and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Isabel Beerman

42 papers receiving 3.0k citations

Hit Papers

Human bone marrow hematopoietic stem cells are increased ... 2010 2026 2015 2020 2011 2010 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
Isabel Beerman United States 21 1.6k 1.1k 967 408 387 45 3.1k
Maria Carolina Florian Germany 21 1.2k 0.8× 978 0.9× 703 0.7× 313 0.8× 304 0.8× 45 2.3k
Yohei Morita Japan 32 2.2k 1.3× 1.9k 1.7× 1.4k 1.5× 632 1.5× 485 1.3× 57 4.4k
Johanna Flach Germany 16 1.5k 0.9× 1.2k 1.1× 681 0.7× 543 1.3× 247 0.6× 31 2.8k
Borja Sáez United States 22 1.7k 1.0× 772 0.7× 492 0.5× 423 1.0× 186 0.5× 41 2.8k
Marieke Essers Germany 23 2.8k 1.8× 1.6k 1.5× 1.5k 1.5× 583 1.4× 386 1.0× 43 5.0k
Bogdan Dumitriu United States 20 726 0.5× 1.3k 1.2× 374 0.4× 413 1.0× 550 1.4× 48 2.5k
Nathan C. Boles United States 21 1.4k 0.9× 1.2k 1.1× 1.1k 1.2× 370 0.9× 199 0.5× 33 2.9k
Ronald van Os Netherlands 35 1.5k 0.9× 999 0.9× 676 0.7× 734 1.8× 927 2.4× 68 3.7k
Hideyuki Oguro Japan 19 1.4k 0.9× 1.2k 1.1× 785 0.8× 467 1.1× 160 0.4× 30 2.7k
Ayako Nakamura‐Ishizu Japan 21 1.0k 0.6× 946 0.9× 538 0.6× 385 0.9× 201 0.5× 43 2.1k

Countries citing papers authored by Isabel Beerman

Since Specialization
Citations

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

Fields of papers citing papers by Isabel Beerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabel Beerman

This figure shows the co-authorship network connecting the top 25 collaborators of Isabel Beerman. A scholar is included among the top collaborators of Isabel Beerman 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 Isabel Beerman. Isabel Beerman 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.
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.
3.
Bodogai, Monica, Bong Soo Park, Chen Chen, et al.. (2025). A distinct population of CD8+ T cells expressing CD39 and CD73 accumulates with age and supports cancer progression. Nature Aging. 5(10). 2055–2069. 1 indexed citations
4.
Beerman, Isabel, et al.. (2024). Cellular stress and epigenetic regulation in adult stem cells. Life Science Alliance. 7(12). e202302083–e202302083. 2 indexed citations
5.
Yanai, Hagai, Bongsoo Park, Hyunwook Koh, et al.. (2024). Short-term periodic restricted feeding elicits metabolome-microbiome signatures with sex dimorphic persistence in primate intervention. Nature Communications. 15(1). 1088–1088. 2 indexed citations
6.
Abdelmohsen, Kotb, Rachel Munk, Dimitrios Tsitsipatis, et al.. (2024). Identification of senescent cell subpopulations by CITE‐seq analysis. Aging Cell. 23(11). e14297–e14297. 6 indexed citations
7.
Arao, Yukitomo, Deborah J. Stumpo, Mark J. Hoenerhoff, et al.. (2023). Lethal eosinophilic crystalline pneumonia in mice expressing a stabilized Csf2 mRNA. The FASEB Journal. 37(8). e23100–e23100. 2 indexed citations
9.
Wang, Yunong, Hagai Yanai, Matthew F. Starost, et al.. (2023). Boosting NAD ameliorates hematopoietic impairment linked to short telomeres in vivo. GeroScience. 45(4). 2213–2228. 15 indexed citations
10.
Yanai, Hagai, Christopher Dunn, Bongsoo Park, et al.. (2022). Male rat leukocyte population dynamics predict a window for intervention in aging. eLife. 11. 3 indexed citations
11.
Chen, Chen, Bong Soo Park, Emeline Ragonnaud, et al.. (2022). Cancer co-opts differentiation of B-cell precursors into macrophage-like cells. Nature Communications. 13(1). 5376–5376. 23 indexed citations
12.
Zong, Le, Bongsoo Park, Hagai Yanai, et al.. (2021). NAD+ augmentation with nicotinamide riboside improves lymphoid potential of Atm−/− and old mice HSCs. SHILAP Revista de lepidopterología. 7(1). 25–25. 16 indexed citations
13.
Gutierrez‐Rodrigues, Fernanda, Isabel Beerman, Emma M. Groarke, et al.. (2021). Utility of plasma cell-free DNA for <i>de novo</i> detection and quantification of clonal hematopoiesis. Haematologica. 107(8). 1815–1826. 5 indexed citations
14.
Luís, Tiago C., Adam C. Wilkinson, Isabel Beerman, Siddhartha Jaiswal, & Liran I. Shlush. (2019). Biological implications of clonal hematopoiesis. Experimental Hematology. 77. 1–5. 22 indexed citations
15.
Yanai, Hagai, et al.. (2019). DNA damage in aging, the stem cell perspective. Human Genetics. 139(3). 309–331. 40 indexed citations
16.
Zhang, Yingying, Jocelyn Charlton, Rahul Karnik, et al.. (2018). Targets and genomic constraints of ectopic Dnmt3b expression. eLife. 7. 28 indexed citations
17.
Gutierrez‐Martinez, Paula, Leah J. Hogdal, Rumani Singh, et al.. (2018). Diminished apoptotic priming and ATM signalling confer a survival advantage onto aged haematopoietic stem cells in response to DNA damage. Nature Cell Biology. 20(4). 413–421. 47 indexed citations
18.
Kokkaliaris, Konstantinos D., Daniel Lucas, Isabel Beerman, David G. Kent, & Leïla Perié. (2016). Understanding hematopoiesis from a single-cell standpoint. Experimental Hematology. 44(6). 447–450. 3 indexed citations
19.
Beerman, Isabel, Jun Seita, Matthew A. Inlay, Irving L. Weissman, & Derrick J. Rossi. (2014). Quiescent Hematopoietic Stem Cells Accumulate DNA Damage during Aging that Is Repaired upon Entry into Cell Cycle. Cell stem cell. 15(1). 37–50. 326 indexed citations
20.
Beerman, Isabel, Deepta Bhattacharya, Sasan Zandi, et al.. (2010). Functionally distinct hematopoietic stem cells modulate hematopoietic lineage potential during aging by a mechanism of clonal expansion. Proceedings of the National Academy of Sciences. 107(12). 5465–5470. 506 indexed citations breakdown →

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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