Thomas Coudrat

1.1k citations
10 papers · 868 · 1 hit paper · h-index 8

Impact in

Papers in

Thomas Coudrat

10 papers receiving 860 citations

Thomas Coudrat's Hit Papers

Phase-plate cryo-EM structure of a class B GPCR–G-protein complex 2017 · 362 citations
3620+3+6Years since publication100200300

Peers

Thomas Coudrat
Comparison fields: 5 of 68
  • Structural Biology 51
  • Cellular and Molecular Neuroscience 524
  • Molecular Biology 773
  • Endocrinology, Diabetes and Metabolism 108
  • Computational Theory and Mathematics 81
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Citations per field
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Citations per year

Countries citing papers authored by Thomas Coudrat

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Coudrat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas Coudrat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas Coudrat Line = papers co-authored together Thomas Coudrat links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Phase-plate cryo-EM structure of a class B GPCR–G-protein complex
Hit paper breakdown →
2017362
2 2016264
3 201579
4 201552
5 201643
6 201842
7 20178
8 20177
9 20166
10 20215

About Thomas Coudrat

Thomas Coudrat is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Radiology, Nuclear Medicine and Imaging, Computational Theory and Mathematics and Endocrinology, Diabetes and Metabolism, having authored 10 papers that have together received 868 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (10 papers), Neuropeptides and Animal Physiology (6 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Computational Drug Discovery Methods (2 papers), Diabetes Treatment and Management (2 papers), Estrogen and related hormone effects (1 paper), Lipid Membrane Structure and Behavior (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Structural Biology (51 citations), Cellular and Molecular Neuroscience (524 citations), Molecular Biology (773 citations), Endocrinology, Diabetes and Metabolism (108 citations) and Computational Theory and Mathematics (81 citations). Thomas Coudrat has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Arthur Christopoulos, Patrick M. Sexton, Meritxell Canals, J. Robert Lane, Denise Wootten, Laurence J. Miller, Sebastian G. B. Furness, David M. Thal, Wolfgang Baumeister and Georgios Skiniotis. Their work appears in journals such as Molecular Pharmacology, Frontiers in Endocrinology, PLoS Computational Biology, Journal of Biological Chemistry and Nature Communications.

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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