James Shorter

26.9k total citations · 9 hit papers
161 papers, 15.9k citations indexed

About

James Shorter is a scholar working on Molecular Biology, Cell Biology and Neurology. According to data from OpenAlex, James Shorter has authored 161 papers receiving a total of 15.9k indexed citations (citations by other indexed papers that have themselves been cited), including 142 papers in Molecular Biology, 46 papers in Cell Biology and 44 papers in Neurology. Recurrent topics in James Shorter's work include RNA Research and Splicing (48 papers), Prion Diseases and Protein Misfolding (46 papers) and Amyotrophic Lateral Sclerosis Research (41 papers). James Shorter is often cited by papers focused on RNA Research and Splicing (48 papers), Prion Diseases and Protein Misfolding (46 papers) and Amyotrophic Lateral Sclerosis Research (41 papers). James Shorter collaborates with scholars based in United States, United Kingdom and Germany. James Shorter's co-authors include Susan Lindquist, Aaron D. Gitler, Oliver D. King, Graham Warren, Edward Gomes, Meredith E. Jackrel, Lin Guo, Leslie A. Lange, Brian S. Johnson and J. Michael McCaffery and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

James Shorter

158 papers receiving 15.7k citations

Hit Papers

Protein Phase Separation: A New Phase in... 2009 2026 2014 2020 2018 2013 2009 2018 2012 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Shorter United States 63 12.8k 4.0k 3.6k 1.7k 1.7k 161 15.9k
Simon Alberti Germany 58 17.2k 1.3× 1.5k 0.4× 2.8k 0.8× 1.1k 0.6× 606 0.4× 106 19.7k
Junmin Peng United States 78 16.9k 1.3× 1.5k 0.4× 3.4k 0.9× 2.3k 1.4× 705 0.4× 257 23.0k
Ron R. Kopito United States 67 14.6k 1.1× 2.5k 0.6× 7.3k 2.0× 3.6k 2.2× 619 0.4× 136 22.6k
Ludo Van Den Bosch Belgium 64 8.6k 0.7× 6.2k 1.5× 1.1k 0.3× 1.9k 1.2× 3.3k 2.0× 283 15.3k
Erika L.F. Holzbaur United States 79 10.5k 0.8× 3.0k 0.8× 9.5k 2.6× 2.5k 1.5× 1.0k 0.6× 205 19.0k
Henning Urlaub Germany 83 20.3k 1.6× 527 0.1× 2.2k 0.6× 1.1k 0.6× 478 0.3× 445 24.9k
Masayuki Miura Japan 64 8.6k 0.7× 640 0.2× 2.3k 0.7× 825 0.5× 267 0.2× 253 13.2k
Giampietro Schiavo United Kingdom 76 9.6k 0.7× 8.0k 2.0× 6.2k 1.7× 2.3k 1.4× 658 0.4× 260 19.7k
Magdalini Polymenidou Switzerland 32 6.7k 0.5× 4.0k 1.0× 494 0.1× 1.2k 0.7× 2.2k 1.3× 56 9.6k
Joost Schymkowitz Belgium 58 10.6k 0.8× 885 0.2× 1.2k 0.3× 3.4k 2.0× 354 0.2× 188 14.3k

Countries citing papers authored by James Shorter

Since Specialization
Citations

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

Fields of papers citing papers by James Shorter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Shorter

This figure shows the co-authorship network connecting the top 25 collaborators of James Shorter. A scholar is included among the top collaborators of James Shorter 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 James Shorter. James Shorter 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.
Reane, Denis Vecellio, Ryan R. Cupo, James Shorter, et al.. (2025). Dependence of mitochondrial calcium signalling and dynamics on the disaggregase, CLPB. Nature Communications. 16(1). 2810–2810. 2 indexed citations
2.
Girdhar, Amandeep, M.E. Cicardi, Miyuki Hayashi, et al.. (2025). NLS-binding deficient Kapβ2 reduces neurotoxicity via selective interaction with C9orf72-ALS/FTD dipeptide repeats. Communications Biology. 8(1). 2–2. 2 indexed citations
3.
Robinson, Emma C., et al.. (2024). Reversing aberrant phase transitions of ALS-linked disease protein FUS with RNA. Biophysical Journal. 123(3). 216a–216a. 1 indexed citations
4.
Khalil, Bilal, et al.. (2024). Nuclear-import receptors as gatekeepers of pathological phase transitions in ALS/FTD. Molecular Neurodegeneration. 19(1). 8–8. 14 indexed citations
5.
Dorweiler, Jane E., et al.. (2024). The middle domain of Hsp104 can ensure substrates are functional after processing. PLoS Genetics. 20(10). e1011424–e1011424. 3 indexed citations
6.
Balendra, Rubika, Igor Ruiz de los Mozos, Hana M. Odeh, et al.. (2023). Transcriptome-wide RNA binding analysis of C9orf72 poly(PR) dipeptides. Life Science Alliance. 6(9). e202201824–e202201824. 5 indexed citations
7.
Wiese, Sebastian, Amandeep Girdhar, Nadine Schwierz, et al.. (2023). Cryo-EM Structure of the Full-length hnRNPA1 Amyloid Fibril. Journal of Molecular Biology. 435(18). 168211–168211. 6 indexed citations
8.
Peinado, Juan R., et al.. (2022). Sequestration of TDP-43 216-414 Aggregates by Cytoplasmic Expression of the proSAAS Chaperone. ACS Chemical Neuroscience. 13(11). 1651–1665. 9 indexed citations
9.
Warren, Julia T., Ryan R. Cupo, David H. Spencer, et al.. (2021). Heterozygous variants of CLPB are a cause of severe congenital neutropenia. Blood. 139(5). 779–791. 24 indexed citations
10.
Hallegger, Martina, Anob M. Chakrabarti, Flora Lee, et al.. (2021). TDP-43 condensation properties specify its RNA-binding and regulatory repertoire. Cell. 184(18). 4680–4696.e22. 137 indexed citations
11.
Fare, Charlotte M., et al.. (2021). Higher-order organization of biomolecular condensates. Open Biology. 11(6). 210137–210137. 111 indexed citations
12.
March, Zachary M., Hanna Kim, Xiaohui Yan, et al.. (2020). Therapeutic genetic variation revealed in diverse Hsp104 homologs. eLife. 9. 23 indexed citations
13.
Fredrickson, Eric K., JiaBei Lin, Edward Chuang, et al.. (2019). The extent of Ssa1/Ssa2 Hsp70 chaperone involvement in nuclear protein quality control degradation varies with the substrate. Molecular Biology of the Cell. 31(3). 221–233. 14 indexed citations
14.
Gates, Stephanie N., Adam L. Yokom, JiaBei Lin, et al.. (2017). Ratchet-like polypeptide translocation mechanism of the AAA+ disaggregase Hsp104. Science. 357(6348). 273–279. 193 indexed citations
15.
Jackrel, Meredith E. & James Shorter. (2017). Protein-Remodeling Factors As Potential Therapeutics for Neurodegenerative Disease. Frontiers in Neuroscience. 11. 99–99. 29 indexed citations
16.
Shorter, James. (2016). Engineering therapeutic protein disaggregases. Molecular Biology of the Cell. 27(10). 1556–1560. 46 indexed citations
17.
DeSantis, Morgan E. & James Shorter. (2012). Hsp104 Drives “Protein-Only” Positive Selection of Sup35 Prion Strains Encoding Strong [PSI]. Chemistry & Biology. 19(11). 1400–1410. 39 indexed citations
18.
Shorter, James. (2010). Emergence and natural selection of drug-resistant prions. Molecular BioSystems. 6(7). 1115–1130. 43 indexed citations
19.
Watt, Brenda, Guillaume van Niel, Douglas M. Fowler, et al.. (2009). N-terminal Domains Elicit Formation of Functional Pmel17 Amyloid Fibrils. Journal of Biological Chemistry. 284(51). 35543–35555. 90 indexed citations
20.
Shorter, James & Susan Lindquist. (2004). Hsp104 Catalyzes Formation and Elimination of Self-Replicating Sup35 Prion Conformers. Science. 304(5678). 1793–1797. 389 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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