Joseph A. Marsh

8.7k total citations · 2 hit papers
92 papers, 5.0k citations indexed

About

Joseph A. Marsh is a scholar working on Molecular Biology, Genetics and Materials Chemistry. According to data from OpenAlex, Joseph A. Marsh has authored 92 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Molecular Biology, 25 papers in Genetics and 25 papers in Materials Chemistry. Recurrent topics in Joseph A. Marsh's work include Protein Structure and Dynamics (38 papers), Enzyme Structure and Function (25 papers) and RNA and protein synthesis mechanisms (22 papers). Joseph A. Marsh is often cited by papers focused on Protein Structure and Dynamics (38 papers), Enzyme Structure and Function (25 papers) and RNA and protein synthesis mechanisms (22 papers). Joseph A. Marsh collaborates with scholars based in United Kingdom, United States and Canada. Joseph A. Marsh's co-authors include Julie D. Forman‐Kay, Sarah A. Teichmann, Benjamin Livesey, Zongchao Jia, Vinay Kumar Singh, Jonathan N. Wells, Sebastian E. Ahnert, György Abrusán, Lukas Gerasimavicius and Carol V. Robinson and has published in prestigious journals such as Science, Cell and Journal of the American Chemical Society.

In The Last Decade

Joseph A. Marsh

89 papers receiving 5.0k citations

Hit Papers

Sensitivity of secondary structure propensities to sequen... 2006 2026 2012 2019 2006 2022 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
Joseph A. Marsh United Kingdom 39 4.1k 1.3k 653 592 541 92 5.0k
Birthe B. Kragelund Denmark 49 5.2k 1.3× 1.4k 1.1× 696 1.1× 373 0.6× 671 1.2× 179 6.9k
J. David Lawson United States 17 4.3k 1.1× 1.4k 1.1× 496 0.8× 354 0.6× 540 1.0× 41 5.3k
Yang Shen United States 23 4.7k 1.2× 1.5k 1.2× 1.3k 2.0× 447 0.8× 416 0.8× 44 5.9k
Robert Konrat Austria 39 3.9k 1.0× 1.1k 0.9× 1.3k 2.0× 343 0.6× 352 0.7× 194 5.3k
Neil A. Farrow United States 30 3.8k 0.9× 1.1k 0.9× 849 1.3× 383 0.6× 463 0.9× 51 5.6k
Pau Bernadó France 44 5.2k 1.3× 2.2k 1.7× 1.1k 1.7× 360 0.6× 462 0.9× 131 6.4k
Stefano Gianni Italy 39 3.8k 0.9× 1.7k 1.3× 360 0.6× 216 0.4× 812 1.5× 172 4.5k
Lawrence P. McIntosh Canada 48 5.8k 1.4× 1.1k 0.8× 683 1.0× 621 1.0× 435 0.8× 145 7.5k
Francisco J. Blanco Spain 42 4.9k 1.2× 1.3k 1.0× 645 1.0× 447 0.8× 276 0.5× 132 5.8k
Jill Trewhella United States 44 4.4k 1.1× 1.9k 1.5× 581 0.9× 316 0.5× 554 1.0× 158 5.7k

Countries citing papers authored by Joseph A. Marsh

Since Specialization
Citations

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

Fields of papers citing papers by Joseph A. Marsh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joseph A. Marsh

This figure shows the co-authorship network connecting the top 25 collaborators of Joseph A. Marsh. A scholar is included among the top collaborators of Joseph A. Marsh 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 Joseph A. Marsh. Joseph A. Marsh 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
2.
Phipson, Belinda, et al.. (2025). Variant scoring tools for deep mutational scanning. Molecular Systems Biology. 21(10). 1293–1305. 1 indexed citations
3.
Deevy, Orla, Jingjing Li, Karsten Hokamp, et al.. (2025). Dominant-negative effects of Weaver syndrome-associated EZH2 variants. Genes & Development. 39(21-22). 1355–1376.
4.
Marsh, Joseph A., et al.. (2025). Prevalence of loss-of-function, gain-of-function and dominant-negative mechanisms across genetic disease phenotypes. Nature Communications. 16(1). 8392–8392.
5.
Procé, Sophie Marion de, José Luis Campos, Alison Meynert, et al.. (2024). Whole genome sequencing enhances molecular diagnosis of primary ciliary dyskinesia. Pediatric Pulmonology. 59(12). 3322–3332. 3 indexed citations
6.
Livesey, Benjamin, et al.. (2024). Deep mutational scanning quantifies DNA binding and predicts clinical outcomes of PAX6 variants. Molecular Systems Biology. 20(7). 825–844. 6 indexed citations
7.
Mohamed, Fawzy & Joseph A. Marsh. (2024). Understanding the heterogeneous performance of variant effect predictors across human protein-coding genes. Scientific Reports. 14(1). 26114–26114. 3 indexed citations
8.
Mouilleron, Stéphane, et al.. (2024). Structural insight into the function of human peptidyl arginine deiminase 6. Computational and Structural Biotechnology Journal. 23. 3258–3269. 2 indexed citations
9.
Thul, Rüdiger, Joseph A. Marsh, Ton Dijkstra, & Kathy Conklin. (2024). Stratified distributional analysis—a novel perspective on RT distributions. Quarterly Journal of Experimental Psychology. 78(8). 1740–1756.
10.
Marsh, Joseph A., et al.. (2023). Hallmarks and evolutionary drivers of cotranslational protein complex assembly. FEBS Journal. 291(16). 3557–3567. 4 indexed citations
11.
Livesey, Benjamin & Joseph A. Marsh. (2023). Advancing variant effect prediction using protein language models. Nature Genetics. 55(9). 1426–1427. 5 indexed citations
12.
Poole, Rebecca, Alison Cozens, Nicola Foulds, et al.. (2023). Expanding the neurodevelopmental phenotype associated with HK1 de novo heterozygous missense variants. European Journal of Medical Genetics. 66(3). 104696–104696. 1 indexed citations
13.
Robertson, Neil, Benjamin Livesey, Robert F. Hillary, et al.. (2022). Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects. Nature Medicine. 28(7). 1439–1446. 59 indexed citations
14.
Welburn, Julie P. I., et al.. (2022). Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations. PLoS Computational Biology. 18(10). e1010611–e1010611. 5 indexed citations
15.
Tarnauskaitė, Žygimantė, Louise S. Bicknell, Joseph A. Marsh, et al.. (2019). Biallelic variants in DNA2 cause microcephalic primordial dwarfism. Human Mutation. 40(8). 1063–1070. 17 indexed citations
16.
Bergendahl, L. Therese, et al.. (2017). The genetic basis and evolution of red blood cell sickling in deer. Nature Ecology & Evolution. 2(2). 367–376. 9 indexed citations
17.
Ahnert, Sebastian E., Joseph A. Marsh, Helena Hernández, Carol V. Robinson, & Sarah A. Teichmann. (2015). Principles of assembly reveal a periodic table of protein complexes. Science. 350(6266). aaa2245–aaa2245. 172 indexed citations
18.
Ahlner, Alexandra, et al.. (2015). Fast and Accurate Resonance Assignment of Small-to-Large Proteins by Combining Automated and Manual Approaches. PLoS Computational Biology. 11(1). e1004022–e1004022. 8 indexed citations
19.
Marsh, Joseph A. & Julie D. Forman‐Kay. (2009). Structure and Disorder in an Unfolded State under Nondenaturing Conditions from Ensemble Models Consistent with a Large Number of Experimental Restraints. Journal of Molecular Biology. 391(2). 359–374. 130 indexed citations
20.
Marsh, Joseph A., et al.. (2007). Synuclein-γ Targeting Peptide Inhibitor that Enhances Sensitivity of Breast Cancer Cells to Antimicrotubule Drugs. Cancer Research. 67(2). 626–633. 50 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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