Leemor Joshua‐Tor

14.3k total citations · 4 hit papers
88 papers, 10.4k citations indexed

About

Leemor Joshua‐Tor is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Leemor Joshua‐Tor has authored 88 papers receiving a total of 10.4k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Molecular Biology, 9 papers in Cancer Research and 8 papers in Oncology. Recurrent topics in Leemor Joshua‐Tor's work include RNA Research and Splicing (24 papers), RNA and protein synthesis mechanisms (19 papers) and RNA Interference and Gene Delivery (14 papers). Leemor Joshua‐Tor is often cited by papers focused on RNA Research and Splicing (24 papers), RNA and protein synthesis mechanisms (19 papers) and RNA Interference and Gene Delivery (14 papers). Leemor Joshua‐Tor collaborates with scholars based in United States, Netherlands and United Kingdom. Leemor Joshua‐Tor's co-authors include Gregory J. Hannon, Ji‐Joon Song, Niraj H. Tolia, Eric J. Enemark, Jidong Liu, Fabiola V. Rivas, Carolyn G. Marsden, Michelle A. Carmell, J. Michael Thomson and Scott M. Hammond and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Leemor Joshua‐Tor

87 papers receiving 10.3k citations

Hit Papers

Argonaute2 Is the Catalytic Engine of Mammalian RNAi 2004 2026 2011 2018 2004 2004 2005 2006 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
Leemor Joshua‐Tor United States 44 8.7k 2.6k 1.9k 865 609 88 10.4k
Tatyana V. Pestova United States 64 13.7k 1.6× 1.1k 0.4× 1.4k 0.7× 921 1.1× 608 1.0× 112 15.8k
Peter R. Cook United Kingdom 65 13.0k 1.5× 1.1k 0.4× 1.7k 0.9× 1.9k 2.2× 494 0.8× 210 14.9k
Yukihide Tomari Japan 47 9.8k 1.1× 3.9k 1.5× 2.4k 1.3× 824 1.0× 687 1.1× 98 11.3k
Wendy V. Gilbert United States 31 9.2k 1.0× 1.1k 0.4× 963 0.5× 1.9k 2.2× 537 0.9× 60 11.1k
R. Daniel Camerini‐Otero United States 59 8.9k 1.0× 1.0k 0.4× 1.6k 0.8× 2.8k 3.2× 547 0.9× 143 10.6k
Katarzyna Bębenek United States 51 7.5k 0.9× 1.3k 0.5× 667 0.3× 1.5k 1.7× 520 0.9× 99 9.1k
Ulrike Kutay Switzerland 56 13.1k 1.5× 1.8k 0.7× 608 0.3× 1.1k 1.3× 591 1.0× 108 14.7k
Hitoshi Kurumizaka Japan 59 9.5k 1.1× 780 0.3× 1.6k 0.8× 1.4k 1.6× 393 0.6× 302 10.5k
Frédéric H.‐T. Allain Switzerland 65 11.2k 1.3× 930 0.4× 733 0.4× 1.1k 1.2× 417 0.7× 180 12.7k
Danesh Moazed United States 65 14.9k 1.7× 954 0.4× 3.7k 1.9× 1.9k 2.1× 534 0.9× 107 16.9k

Countries citing papers authored by Leemor Joshua‐Tor

Since Specialization
Citations

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

Fields of papers citing papers by Leemor Joshua‐Tor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leemor Joshua‐Tor. 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 Leemor Joshua‐Tor. The network helps show where Leemor Joshua‐Tor may publish in the future.

Co-authorship network of co-authors of Leemor Joshua‐Tor

This figure shows the co-authorship network connecting the top 25 collaborators of Leemor Joshua‐Tor. A scholar is included among the top collaborators of Leemor Joshua‐Tor 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 Leemor Joshua‐Tor. Leemor Joshua‐Tor 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.
Garg, Ankur, Kin Fan On, Yang Xiao, et al.. (2025). The molecular basis of Human FN3K mediated phosphorylation of glycated substrates. Nature Communications. 16(1). 941–941. 1 indexed citations
2.
Alpsoy, Aktan, Jonathan J. Ipsaro, Damianos Skopelitis, et al.. (2025). Structural basis of DNA-dependent coactivator recruitment by the tuft cell master regulator POU2F3. Cell Reports. 44(11). 116572–116572.
3.
Yang, Bing, et al.. (2024). Catalytic residues of microRNA Argonautes play a modest role in microRNA star strand destabilization in C. elegans. Nucleic Acids Research. 52(9). 4985–5001. 2 indexed citations
4.
Garg, Ankur, et al.. (2024). The structural landscape of Microprocessor-mediated processing of pri-let-7 miRNAs. Molecular Cell. 84(21). 4175–4190.e6. 7 indexed citations
5.
Stec, Natalia, Jing Wang, M. Jaremko, et al.. (2023). A circadian-like gene network programs the timing and dosage of heterochronic miRNA transcription during C. elegans development. Developmental Cell. 58(22). 2563–2579.e8. 13 indexed citations
6.
Ipsaro, Jonathan J., et al.. (2023). Manipulating PTPRD function with ectodomain antibodies. Genes & Development. 37(15-16). 743–759. 4 indexed citations
7.
8.
Wu, Xiaoli, Xue‐Yan He, Jonathan J. Ipsaro, et al.. (2022). OCA-T1 and OCA-T2 are coactivators of POU2F3 in the tuft cell lineage. Nature. 607(7917). 169–175. 48 indexed citations
9.
Jaremko, M., Kin Fan On, Dennis R. Thomas, Bruce Stillman, & Leemor Joshua‐Tor. (2020). The dynamic nature of the human origin recognition complex revealed through five cryoEM structures. eLife. 9. 22 indexed citations
10.
Jung, James, Timothy Grant, Dennis R. Thomas, et al.. (2019). High-resolution cryo-EM structures of outbreak strain human norovirus shells reveal size variations. Proceedings of the National Academy of Sciences. 116(26). 12828–12832. 53 indexed citations
11.
Lee, Seung‐Jae, et al.. (2014). Dynamic look at DNA unwinding by a replicative helicase. Proceedings of the National Academy of Sciences. 111(9). E827–35. 54 indexed citations
12.
Elkayam, Elad, Claus‐D. Kuhn, Ante Tocilj, et al.. (2012). The Structure of Human Argonaute-2 in Complex with miR-20a. Cell. 150(1). 233–233. 11 indexed citations
13.
Elkayam, Elad, Claus‐D. Kuhn, Ante Tocilj, et al.. (2012). The Structure of Human Argonaute-2 in Complex with miR-20a. Cell. 150(1). 100–110. 455 indexed citations
14.
Kumar, P. Rajesh, Yao Yu, Rolf Sternglanz, Stephen Albert Johnston, & Leemor Joshua‐Tor. (2008). NADP Regulates the Yeast GAL Induction System. Science. 319(5866). 1090–1092. 43 indexed citations
15.
Yigit, Erbay, Pedro J. Batista, Yanxia Bei, et al.. (2006). Analysis of the C. elegans Argonaute Family Reveals that Distinct Argonautes Act Sequentially during RNAi. Cell. 127(4). 747–757. 492 indexed citations breakdown →
16.
Tolia, Niraj H., Eric J. Enemark, B. Kim Lee Sim, & Leemor Joshua‐Tor. (2005). Structural Basis for the EBA-175 Erythrocyte Invasion Pathway of the Malaria Parasite Plasmodium falciparum. Cell. 122(2). 183–193. 260 indexed citations
17.
Song, Ji‐Joon, et al.. (2004). Crystal Structure of Argonaute and Its Implications for RISC Slicer Activity. Science. 305(5689). 1434–1437. 1105 indexed citations breakdown →
18.
Liu, Jidong, Michelle A. Carmell, Fabiola V. Rivas, et al.. (2004). Argonaute2 Is the Catalytic Engine of Mammalian RNAi. Science. 305(5689). 1437–1441. 2053 indexed citations breakdown →
19.
Joshua‐Tor, Leemor. (2004). siRNAs at RISC. Structure. 12(7). 1120–1122. 4 indexed citations
20.
Schlessman, J.L., et al.. (1998). Conformational variability in structures of the nitrogenase iron proteins from Azotobacter vinelandii and Clostridium pasteurianum. Journal of Molecular Biology. 280(4). 669–685. 118 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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