Scott A. Showalter

2.3k total citations
64 papers, 1.7k citations indexed

About

Scott A. Showalter is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Scott A. Showalter has authored 64 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 19 papers in Materials Chemistry and 14 papers in Spectroscopy. Recurrent topics in Scott A. Showalter's work include Protein Structure and Dynamics (26 papers), RNA Research and Splicing (22 papers) and RNA and protein synthesis mechanisms (19 papers). Scott A. Showalter is often cited by papers focused on Protein Structure and Dynamics (26 papers), RNA Research and Splicing (22 papers) and RNA and protein synthesis mechanisms (19 papers). Scott A. Showalter collaborates with scholars based in United States, France and Germany. Scott A. Showalter's co-authors include Rafael Brüschweiler, Eric Gibbs, Erik C. Cook, Kathleen B. Hall, Eric Johnson, Debashish Sahu, Chad W. Lawrence, Emily R. Featherston, Joseph A. Cotruvo and Dawei Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Scott A. Showalter

64 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott A. Showalter United States 24 1.4k 494 420 109 104 64 1.7k
Thomas Szyperski United States 26 2.4k 1.7× 661 1.3× 696 1.7× 95 0.9× 89 0.9× 63 3.1k
Gregg Siegal Netherlands 27 1.7k 1.2× 305 0.6× 284 0.7× 120 1.1× 40 0.4× 59 2.2k
Dinesh K. Sukumaran United States 27 1.1k 0.8× 513 1.0× 378 0.9× 60 0.6× 54 0.5× 44 2.0k
Leszek Poppe United States 26 1.4k 1.0× 228 0.5× 330 0.8× 111 1.0× 69 0.7× 55 2.1k
Matthew J. Cliff United Kingdom 29 1.7k 1.2× 615 1.2× 312 0.7× 278 2.6× 51 0.5× 73 2.4k
Renee Otten United States 23 1.4k 1.0× 424 0.9× 261 0.6× 126 1.2× 62 0.6× 34 1.8k
Peter F. Flynn United States 26 1.2k 0.9× 263 0.5× 327 0.8× 254 2.3× 133 1.3× 41 1.6k
Ewen Lescop France 24 1.3k 0.9× 248 0.5× 322 0.8× 115 1.1× 39 0.4× 59 1.9k
Arnout P. Kalverda United Kingdom 23 1.6k 1.1× 388 0.8× 196 0.5× 208 1.9× 99 1.0× 54 2.0k
Thomas Raschle Switzerland 17 1.3k 0.9× 352 0.7× 227 0.5× 83 0.8× 61 0.6× 23 1.7k

Countries citing papers authored by Scott A. Showalter

Since Specialization
Citations

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

Fields of papers citing papers by Scott A. Showalter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott A. Showalter. 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 Scott A. Showalter. The network helps show where Scott A. Showalter may publish in the future.

Co-authorship network of co-authors of Scott A. Showalter

This figure shows the co-authorship network connecting the top 25 collaborators of Scott A. Showalter. A scholar is included among the top collaborators of Scott A. Showalter 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 Scott A. Showalter. Scott A. Showalter 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.
Chen, Wei, Tatiana N. Laremore, Neela H. Yennawar, & Scott A. Showalter. (2025). Phosphorylation modulates secondary structure of intrinsically disorder regions in RNA polymerase II. Journal of Biological Chemistry. 301(6). 108533–108533. 1 indexed citations
2.
Chen, Wei, et al.. (2024). From molecular descriptions to cellular functions of intrinsically disordered protein regions. PubMed. 5(4). 41306–41306. 1 indexed citations
3.
Mittal, Jeetain, et al.. (2024). Acetylation-Dependent Compaction of the Histone H4 Tail Ensemble. The Journal of Physical Chemistry B. 128(43). 10636–10649. 4 indexed citations
4.
Yennawar, Neela H., Varun V. Gadkari, Brandon T. Ruotolo, et al.. (2024). Molecular insights into the interaction between a disordered protein and a folded RNA. Proceedings of the National Academy of Sciences. 121(49). e2409139121–e2409139121. 6 indexed citations
5.
Showalter, Scott A., et al.. (2023). Phase separation promotes a highly active oligomeric scaffold of the MLL1 core complex for regulation of histone H3K4 methylation. Journal of Biological Chemistry. 299(10). 105204–105204. 2 indexed citations
6.
Showalter, Scott A., et al.. (2021). Transient Electrostatic Interactions between Fcp1 and Rap74 Bias the Conformational Ensemble of the Complex with Minimal Impact on Binding Affinity. The Journal of Physical Chemistry B. 125(39). 10917–10927. 2 indexed citations
7.
Cosgrove, Michael S., et al.. (2021). Probing multiple enzymatic methylation events in real time with NMR spectroscopy. Biophysical Journal. 120(21). 4710–4721. 9 indexed citations
8.
Sabri, Nafiseh, et al.. (2021). Intrinsically disordered substrates dictate SPOP subnuclear localization and ubiquitination activity. Journal of Biological Chemistry. 296. 100693–100693. 12 indexed citations
9.
Pabit, Suzette A., et al.. (2020). Elucidating the Role of Microprocessor Protein DGCR8 in Bending RNA Structures. Biophysical Journal. 119(12). 2524–2536. 4 indexed citations
10.
Cook, Erik C., Tawanda J. Zimudzi, Scott A. Showalter, et al.. (2020). Ultrasound-Guided Cytosolic Protein Delivery via Transient Fluorous Masks. ACS Nano. 14(4). 4061–4073. 39 indexed citations
11.
Cook, Erik C., Emily R. Featherston, Scott A. Showalter, & Joseph A. Cotruvo. (2018). Structural Basis for Rare Earth Element Recognition by Methylobacterium extorquens Lanmodulin. Biochemistry. 58(2). 120–125. 105 indexed citations
12.
Cook, Erik C., et al.. (2018). Solution Ensemble of the C-Terminal Domain from the Transcription Factor Pdx1 Resembles an Excluded Volume Polymer. The Journal of Physical Chemistry B. 123(1). 106–116. 10 indexed citations
13.
Gibbs, Eric, Bede Portz, Michael J. Fisher, et al.. (2017). Phosphorylation induces sequence-specific conformational switches in the RNA polymerase II C-terminal domain. Nature Communications. 8(1). 15233–15233. 64 indexed citations
14.
15.
Gibbs, Eric, Erik C. Cook, & Scott A. Showalter. (2017). Application of NMR to studies of intrinsically disordered proteins. Archives of Biochemistry and Biophysics. 628. 57–70. 77 indexed citations
16.
Portz, Bede, Eric Gibbs, Joshua E. Mayfield, et al.. (2017). Structural heterogeneity in the intrinsically disordered RNA polymerase II C-terminal domain. Nature Communications. 8(1). 15231–15231. 50 indexed citations
17.
Gibbs, Eric & Scott A. Showalter. (2015). Quantitative Biophysical Characterization of Intrinsically Disordered Proteins. Biochemistry. 54(6). 1314–1326. 41 indexed citations
18.
Gibbs, Eric, et al.. (2015). A primer for carbon‐detected NMR applications to intrinsically disordered proteins in solution. Concepts in Magnetic Resonance Part A. 44(1). 54–66. 36 indexed citations
19.
Sahu, Debashish, et al.. (2013). Generating NMR chemical shift assignments of intrinsically disordered proteins using carbon-detected NMR methods. Analytical Biochemistry. 449. 17–25. 42 indexed citations
20.

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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