Leah Randles

1.4k total citations · 1 hit paper
9 papers, 1.1k citations indexed

About

Leah Randles is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Leah Randles has authored 9 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Epidemiology. Recurrent topics in Leah Randles's work include Ubiquitin and proteasome pathways (7 papers), Autophagy in Disease and Therapy (3 papers) and Genetics and Neurodevelopmental Disorders (2 papers). Leah Randles is often cited by papers focused on Ubiquitin and proteasome pathways (7 papers), Autophagy in Disease and Therapy (3 papers) and Genetics and Neurodevelopmental Disorders (2 papers). Leah Randles collaborates with scholars based in United States, Germany and Croatia. Leah Randles's co-authors include Kylie J. Walters, Naixia Zhang, Xiang Chen, Ivan Đikić, Daniel Finley, Koraljka Husnjak, Suzanne Elsasser, Kay Hofmann, Yuan Shi and M. Groll and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Leah Randles

9 papers receiving 1.1k citations

Hit Papers

Proteasome subunit Rpn13 is a novel ubiquitin receptor 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leah Randles United States 8 1.1k 373 335 334 127 9 1.1k
Robert Oania United States 9 1.7k 1.6× 458 1.2× 619 1.8× 462 1.4× 230 1.8× 9 1.8k
Ellen A. Goodall United States 7 843 0.8× 202 0.5× 295 0.9× 263 0.8× 96 0.8× 7 969
Richard G. Yau United States 7 1.1k 1.0× 263 0.7× 264 0.8× 268 0.8× 71 0.6× 8 1.3k
Rebecca Welchman United Kingdom 7 818 0.8× 242 0.6× 235 0.7× 174 0.5× 82 0.6× 8 971
Justin M. Reitsma United States 18 921 0.9× 291 0.8× 178 0.5× 413 1.2× 70 0.6× 30 1.3k
Vicença Ustrell United States 9 1.4k 1.3× 419 1.1× 519 1.5× 374 1.1× 180 1.4× 9 1.4k
Frank Zühl Germany 6 1.4k 1.3× 516 1.4× 430 1.3× 259 0.8× 139 1.1× 8 1.5k
Alex C. Faesen Germany 13 1.1k 1.0× 313 0.8× 412 1.2× 156 0.5× 139 1.1× 17 1.2k
Kee Min Woo South Korea 7 899 0.9× 340 0.9× 296 0.9× 187 0.6× 98 0.8× 9 1.0k

Countries citing papers authored by Leah Randles

Since Specialization
Citations

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

Fields of papers citing papers by Leah Randles

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leah Randles

This figure shows the co-authorship network connecting the top 25 collaborators of Leah Randles. A scholar is included among the top collaborators of Leah Randles 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 Leah Randles. Leah Randles is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Lu, Xiuxiu, Urszula Nowicka, Fen Liu, et al.. (2017). Structure of the Rpn13-Rpn2 complex provides insights for Rpn13 and Uch37 as anticancer targets. Nature Communications. 8(1). 15540–15540. 61 indexed citations
2.
Randles, Leah, Ravi Anchoori, Richard B.S. Roden, & Kylie J. Walters. (2016). The Proteasome Ubiquitin Receptor hRpn13 and Its Interacting Deubiquitinating Enzyme Uch37 Are Required for Proper Cell Cycle Progression. Journal of Biological Chemistry. 291(16). 8773–8783. 45 indexed citations
3.
Chen, Xiang, Leah Randles, Ke Shi, et al.. (2016). Structures of Rpn1 T1:Rad23 and hRpn13:hPLIC2 Reveal Distinct Binding Mechanisms between Substrate Receptors and Shuttle Factors of the Proteasome. Structure. 24(8). 1257–1270. 62 indexed citations
4.
Nowicka, Urszula, Leah Randles, Xiaoshan Shi, et al.. (2015). Mycobacterium tuberculosis copper-regulated protein SocB is an intrinsically disordered protein that folds upon interaction with a synthetic phospholipid bilayer. Proteins Structure Function and Bioinformatics. 84(2). 193–200. 5 indexed citations
5.
Hennig, Janosch, Sjoerd J. de Vries, Leah Randles, et al.. (2012). MTMDAT-HADDOCK: High-throughput, protein complex structure modeling based on limited proteolysis and mass spectrometry. BMC Structural Biology. 12(1). 29–29. 12 indexed citations
6.
Randles, Leah. (2012). Ubiquitin and its binding domains. Frontiers in bioscience. 17(7). 2140–2140. 40 indexed citations
7.
Zhang, Naixia, Qinghua Wang, Aaron Ehlinger, et al.. (2009). Structure of the S5a:K48-Linked Diubiquitin Complex and Its Interactions with Rpn13. Molecular Cell. 35(3). 280–290. 118 indexed citations
8.
Husnjak, Koraljka, Suzanne Elsasser, Naixia Zhang, et al.. (2008). Proteasome subunit Rpn13 is a novel ubiquitin receptor. Nature. 453(7194). 481–488. 514 indexed citations breakdown →
9.
Schreiner, Patrick, Xiang Chen, Koraljka Husnjak, et al.. (2008). Ubiquitin docking at the proteasome through a novel pleckstrin-homology domain interaction. Nature. 453(7194). 548–552. 260 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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