Rhett A. Kovall

3.4k total citations
50 papers, 2.4k citations indexed

About

Rhett A. Kovall is a scholar working on Molecular Biology, Genetics and Cell Biology. According to data from OpenAlex, Rhett A. Kovall has authored 50 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Cell Biology. Recurrent topics in Rhett A. Kovall's work include Developmental Biology and Gene Regulation (28 papers), Genomics and Chromatin Dynamics (21 papers) and RNA Research and Splicing (14 papers). Rhett A. Kovall is often cited by papers focused on Developmental Biology and Gene Regulation (28 papers), Genomics and Chromatin Dynamics (21 papers) and RNA Research and Splicing (14 papers). Rhett A. Kovall collaborates with scholars based in United States, Germany and United Kingdom. Rhett A. Kovall's co-authors include Brian W. Matthews, Jeffrey J. Wilson, Wayne A. Hendrickson, Stephen C. Blacklow, Brian Gebelein, David Sprinzak, Raphael Kopan, Zhenyu Yuan, David R. Friedmann and K. Christopher Min and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Rhett A. Kovall

46 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rhett A. Kovall United States	26	2.0k	280	183	162	148	50	2.4k
Mitsuhiro Shimizu Japan	21	1.9k 1.0×	310 1.1×	148 0.8×	100 0.6×	198 1.3×	53	2.4k
Yuliang Wu Canada	25	2.3k 1.2×	382 1.4×	136 0.7×	166 1.0×	94 0.6×	67	2.7k
Takayuki Suzuki Japan	21	2.3k 1.2×	425 1.5×	400 2.2×	167 1.0×	103 0.7×	97	3.0k
Kevin Blackburn United States	27	2.0k 1.0×	451 1.6×	412 2.3×	262 1.6×	186 1.3×	50	3.2k
Yegor Vassetzky France	35	2.7k 1.4×	404 1.4×	456 2.5×	168 1.0×	232 1.6×	160	3.4k
Sébastien Fribourg France	25	2.2k 1.1×	239 0.9×	192 1.0×	136 0.8×	114 0.8×	52	2.5k
G. Sebastiaan Winkler United Kingdom	28	2.4k 1.2×	214 0.8×	347 1.9×	127 0.8×	234 1.6×	53	2.8k
Lina Li China	26	1.2k 0.6×	165 0.6×	284 1.6×	90 0.6×	150 1.0×	90	1.7k

Countries citing papers authored by Rhett A. Kovall

Since Specialization

Citations

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

Fields of papers citing papers by Rhett A. Kovall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rhett A. Kovall

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

All Works

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20 of 20 papers shown

Riccetti, Matthew, Qin Shen, Joseph Salomone, et al.. (2025). Modelling a pathological GSX2 variant that selectively alters DNA binding reveals hypomorphic mouse brain defects. Disease Models & Mechanisms. 18(2).

Yuan, Zhenyu, Benjamin R. Bowen, Hee‐Woong Lim, et al.. (2025). Defective Notch1 signaling in endothelial cells drives pathogenesis in a mouse model of Adams-Oliver syndrome. Journal of Clinical Investigation. 135(23).

Yuan, Zhenyu, et al.. (2024). Cooperative Gsx2–DNA binding requires DNA bending and a novel Gsx2 homeodomain interface. Nucleic Acids Research. 52(13). 7987–8002. 3 indexed citations

Kovall, Rhett A., et al.. (2024). Loss of Notch dimerization perturbs intestinal homeostasis by a mechanism involving HDAC activity. PLoS Genetics. 20(12). e1011486–e1011486.

Yuan, Zhenyu, David Cheung, Hee‐Woong Lim, et al.. (2023). Prediction of cooperative homeodomain DNA binding sites from high-throughput-SELEX data. Nucleic Acids Research. 51(12). 6055–6072. 6 indexed citations

Chandra, Harish, Rhett A. Kovall, Jagjit S. Yadav, & Xingmin Sun. (2023). Host Immune Responses to Surface S-Layer Proteins (SLPs) of Clostridioides difficile. Microorganisms. 11(2). 380–380. 4 indexed citations

Kovall, Rhett A., et al.. (2023). A novel chemical attack on Notch-mediated transcription by targeting the NACK ATPase. Molecular Therapy — Oncolytics. 28. 307–320. 2 indexed citations

Hall, Daniel, Benedetto Daniele Giaimo, Sung Soo Park, et al.. (2022). The structure, binding and function of a Notch transcription complex involving RBPJ and the epigenetic reader protein L3MBTL3. Nucleic Acids Research. 50(22). 13083–13099. 5 indexed citations

Kuang, Yi, Yoshinobu Odaka, Emily Harding‐Theobald, et al.. (2022). A Drosophila Su(H) model of Adams-Oliver Syndrome reveals cofactor titration as a mechanism underlying developmental defects. PLoS Genetics. 18(8). e1010335–e1010335. 9 indexed citations

10.

Landor, Sebastian K.-J., Niina M. Santio, Daniel Hall, et al.. (2021). PIM-induced phosphorylation of Notch3 promotes breast cancer tumorigenicity in a CSL-independent fashion. Journal of Biological Chemistry. 296. 100593–100593. 11 indexed citations

11.

Kuang, Yi, Matthew T. Weirauch, Raphael Kopan, et al.. (2021). Enhancers with cooperative Notch binding sites are more resistant to regulation by the Hairless co-repressor. PLoS Genetics. 17(9). e1009039–e1009039. 7 indexed citations

12.

Hass, Matthew R., Praneet Chaturvedi, Sarah Stein, et al.. (2020). Notch dimerization and gene dosage are important for normal heart development, intestinal stem cell maintenance, and splenic marginal zone B-cell homeostasis during mite infestation. PLoS Biology. 18(10). e3000850–e3000850. 16 indexed citations

13.

Oswald, Franz & Rhett A. Kovall. (2018). CSL-Associated Corepressor and Coactivator Complexes. Advances in experimental medicine and biology. 1066. 279–295. 28 indexed citations

14.

Kovall, Rhett A., Brian Gebelein, David Sprinzak, & Raphael Kopan. (2017). The Canonical Notch Signaling Pathway: Structural and Biochemical Insights into Shape, Sugar, and Force. Developmental Cell. 41(3). 228–241. 280 indexed citations

15.

Torella, Rubben, Jinghua Li, Robert Stojnic, et al.. (2014). A combination of computational and experimental approaches identifies DNA sequence constraints associated with target site binding specificity of the transcription factor CSL. Nucleic Acids Research. 42(16). 10550–10563. 12 indexed citations

16.

Yuan, Zhenyu, et al.. (2013). Structure and Function of the CSL-KyoT2 Corepressor Complex: A Negative Regulator of Notch Signaling. Structure. 22(1). 70–81. 44 indexed citations

17.

Yuan, Zhenyu, et al.. (2012). Characterization of CSL (CBF-1, Su(H), Lag-1) Mutants Reveals Differences in Signaling Mediated by Notch1 and Notch2. Journal of Biological Chemistry. 287(42). 34904–34916. 35 indexed citations

18.

Yuan, Zhenyu, et al.. (2011). Transcriptional Repression in the Notch Pathway. Journal of Biological Chemistry. 286(17). 14892–14902. 43 indexed citations

19.

Friedmann, David R. & Rhett A. Kovall. (2009). Thermodynamic and structural insights into CSL‐DNA complexes. Protein Science. 19(1). 34–46. 34 indexed citations

20.

Kovall, Rhett A.. (2008). More complicated than it looks: assembly of Notch pathway transcription complexes. Oncogene. 27(38). 5099–5109. 134 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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