Uri Ben‐David

10.1k total citations · 5 hit papers
47 papers, 4.5k citations indexed

About

Uri Ben‐David is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Uri Ben‐David has authored 47 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 13 papers in Cancer Research and 10 papers in Cell Biology. Recurrent topics in Uri Ben‐David's work include Pluripotent Stem Cells Research (22 papers), CRISPR and Genetic Engineering (18 papers) and Cancer Genomics and Diagnostics (13 papers). Uri Ben‐David is often cited by papers focused on Pluripotent Stem Cells Research (22 papers), CRISPR and Genetic Engineering (18 papers) and Cancer Genomics and Diagnostics (13 papers). Uri Ben‐David collaborates with scholars based in Israel, United States and United Kingdom. Uri Ben‐David's co-authors include Nissim Benvenisty, Angelika Amon, Yoav Mayshar, Todd R. Golub, Rameen Beroukhim, Amander T. Clark, William E. Lowry, Benjamin Yakir, Kathrin Plath and Neta Lavon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Genetics.

In The Last Decade

Uri Ben‐David

45 papers receiving 4.4k citations

Hit Papers

The tumorigenicity of human embryonic and induced pluripo... 2010 2026 2015 2020 2011 2010 2017 2019 2022 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
Uri Ben‐David Israel 25 3.1k 831 795 615 576 47 4.5k
Iacovos P. Michael Canada 28 2.6k 0.8× 1.1k 1.3× 501 0.6× 396 0.6× 483 0.8× 43 4.6k
Esther Danenberg Netherlands 9 3.4k 1.1× 2.0k 2.4× 600 0.8× 642 1.0× 732 1.3× 9 5.1k
Mandar D. Muzumdar United States 14 2.9k 0.9× 713 0.9× 480 0.6× 459 0.7× 621 1.1× 21 4.5k
Mark A. LaBarge United States 26 2.1k 0.7× 1.3k 1.5× 450 0.6× 474 0.8× 264 0.5× 76 3.5k
Akiko Shimamura United States 40 4.0k 1.3× 778 0.9× 498 0.6× 415 0.7× 2.0k 3.4× 128 6.6k
Daylon James United States 19 2.4k 0.8× 361 0.4× 335 0.4× 783 1.3× 251 0.4× 40 3.9k
Jacob Zucker United States 6 4.0k 1.3× 384 0.5× 386 0.5× 472 0.8× 451 0.8× 9 4.4k
Takumi Era Japan 35 3.0k 1.0× 297 0.4× 257 0.3× 829 1.3× 482 0.8× 91 4.4k
Valérie Kouskoff United Kingdom 42 4.6k 1.5× 516 0.6× 539 0.7× 715 1.2× 467 0.8× 96 7.2k
Sridaran Natesan United States 16 3.9k 1.2× 449 0.5× 395 0.5× 369 0.6× 758 1.3× 24 4.4k

Countries citing papers authored by Uri Ben‐David

Since Specialization
Citations

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

Fields of papers citing papers by Uri Ben‐David

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Uri Ben‐David. 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 Uri Ben‐David. The network helps show where Uri Ben‐David may publish in the future.

Co-authorship network of co-authors of Uri Ben‐David

This figure shows the co-authorship network connecting the top 25 collaborators of Uri Ben‐David. A scholar is included among the top collaborators of Uri Ben‐David 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 Uri Ben‐David. Uri Ben‐David 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
2.
Sinha, Sanju, Sumeet Patiyal, Jianhua Zhao, et al.. (2025). DeepTarget predicts anti-cancer mechanisms of action of small molecules by integrating drug and genetic screens. npj Precision Oncology. 9(1). 340–340.
3.
Nair, Nishanth Ulhas, Alejandro A. Schäffer, E. Michael Gertz, et al.. (2024). Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma. Cancer Research. 84(20). 3464–3477. 8 indexed citations
4.
Okada, Hajime, et al.. (2024). Aneuploidy as a driver of human cancer. Nature Genetics. 56(10). 2014–2026. 9 indexed citations
5.
Rozenblum, Nir, et al.. (2024). Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes. Genome biology. 25(1). 95–95. 6 indexed citations
6.
Chang, Tiangen, Yingying Cao, Eldad D. Shulman, et al.. (2023). Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations. npj Precision Oncology. 7(1). 54–54. 12 indexed citations
7.
Nahmad, Alessio D., Eli Reuveni, Tamar Tenne, et al.. (2022). Frequent aneuploidy in primary human T cells after CRISPR–Cas9 cleavage. Nature Biotechnology. 40(12). 1807–1813. 122 indexed citations breakdown →
8.
Cohen‐Sharir, Yael & Uri Ben‐David. (2021). Relevance of aneuploidy for cancer therapies targeting the spindle assembly checkpoint and KIF18A. Molecular & Cellular Oncology. 8(3). 1915075–1915075. 3 indexed citations
9.
Enache, Oana M., Verónica Rendo, Mai Abdusamad, et al.. (2020). Author Correction: Cas9 activates the p53 pathway and selects for p53-inactivating mutations. Nature Genetics. 52(7). 748–749. 10 indexed citations
10.
Ben‐David, Uri & Angelika Amon. (2019). Context is everything: aneuploidy in cancer. Nature Reviews Genetics. 21(1). 44–62. 382 indexed citations breakdown →
11.
Abdeen, Suhaib K., et al.. (2018). Somatic loss of WWOX is associated with TP53 perturbation in basal-like breast cancer. Cell Death and Disease. 9(8). 832–832. 22 indexed citations
12.
Andrews, Peter W., Uri Ben‐David, Nissim Benvenisty, et al.. (2017). Assessing the Safety of Human Pluripotent Stem Cells and Their Derivatives for Clinical Applications. Stem Cell Reports. 9(1). 1–4. 92 indexed citations
13.
Bi, Wenya Linda, Peleg Horowitz, Noah F. Greenwald, et al.. (2016). Landscape of Genomic Alterations in Pituitary Adenomas. Clinical Cancer Research. 23(7). 1841–1851. 88 indexed citations
14.
Ben‐David, Uri, Gavin Ha, Prasidda Khadka, et al.. (2016). The landscape of chromosomal aberrations in breast cancer mouse models reveals driver-specific routes to tumorigenesis. Nature Communications. 7(1). 12160–12160. 37 indexed citations
15.
Ben‐David, Uri, Tamar Golan‐Lev, Payal Arora, et al.. (2013). Selective Elimination of Human Pluripotent Stem Cells by an Oleate Synthesis Inhibitor Discovered in a High-Throughput Screen. Cell stem cell. 12(2). 167–179. 250 indexed citations
16.
Ben‐David, Uri, et al.. (2013). Immunologic and chemical targeting of the tight-junction protein Claudin-6 eliminates tumorigenic human pluripotent stem cells. Nature Communications. 4(1). 1992–1992. 126 indexed citations
17.
Lee, Peiyee, Nathan Martin, Kotoka Nakamura, et al.. (2013). SMRT compounds abrogate cellular phenotypes of ataxia telangiectasia in neural derivatives of patient-specific hiPSCs. Nature Communications. 4(1). 1824–1824. 32 indexed citations
18.
Ben‐David, Uri, Oded Kopper, & Nissim Benvenisty. (2012). Expanding the Boundaries of Embryonic Stem Cells. Cell stem cell. 10(6). 666–677. 51 indexed citations
19.
Ben‐David, Uri, Yoav Mayshar, & Nissim Benvenisty. (2011). Large-Scale Analysis Reveals Acquisition of Lineage-Specific Chromosomal Aberrations in Human Adult Stem Cells. Cell stem cell. 9(2). 97–102. 197 indexed citations
20.
Goldring, Christopher E., Paul Duffy, Nissim Benvenisty, et al.. (2011). Assessing the Safety of Stem Cell Therapeutics. Cell stem cell. 9(2). 176–176. 7 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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