Patrick Barth

4.5k total citations
54 papers, 2.8k citations indexed

About

Patrick Barth is a scholar working on Molecular Biology, Cell Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Patrick Barth has authored 54 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 16 papers in Cell Biology and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Patrick Barth's work include Aldose Reductase and Taurine (15 papers), Receptor Mechanisms and Signaling (14 papers) and Protein Structure and Dynamics (10 papers). Patrick Barth is often cited by papers focused on Aldose Reductase and Taurine (15 papers), Receptor Mechanisms and Signaling (14 papers) and Protein Structure and Dynamics (10 papers). Patrick Barth collaborates with scholars based in United States, France and Switzerland. Patrick Barth's co-authors include David Baker, A. Podjarny, Jack Schonbrun, Dino Moras, Kuang-Yui Michael Chen, F. Favier, A. Mitschler, Björn Wallner, Tom Alber and J.F. Biellmann and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Patrick Barth

52 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patrick Barth United States 27 1.9k 707 425 276 225 54 2.8k
John B. C. Findlay United Kingdom 35 2.5k 1.3× 503 0.7× 734 1.7× 220 0.8× 217 1.0× 139 3.8k
Hugo L. Monaco Italy 31 2.2k 1.1× 514 0.7× 214 0.5× 487 1.8× 189 0.8× 84 3.4k
Elisabeth P. Carpenter United Kingdom 35 2.6k 1.3× 235 0.3× 442 1.0× 309 1.1× 219 1.0× 66 3.7k
Carola Hunte Germany 41 5.6k 2.9× 465 0.7× 502 1.2× 444 1.6× 267 1.2× 94 6.8k
A. Weichsel United States 31 1.8k 0.9× 1.1k 1.5× 200 0.5× 387 1.4× 121 0.5× 55 3.1k
Petri Kursula Finland 33 2.3k 1.2× 539 0.8× 811 1.9× 397 1.4× 151 0.7× 150 3.5k
Joachim Krebs Switzerland 27 2.3k 1.2× 567 0.8× 345 0.8× 303 1.1× 242 1.1× 63 3.2k
E.S. Kempner United States 35 3.1k 1.6× 456 0.6× 749 1.8× 305 1.1× 232 1.0× 98 4.1k
Sonia R. Anderson United States 27 1.4k 0.7× 492 0.7× 251 0.6× 250 0.9× 261 1.2× 61 2.3k
Michel Vincent France 33 2.5k 1.3× 365 0.5× 293 0.7× 170 0.6× 195 0.9× 120 3.3k

Countries citing papers authored by Patrick Barth

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Barth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Barth

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Barth. A scholar is included among the top collaborators of Patrick Barth 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 Patrick Barth. Patrick Barth 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.
Conflitti, Paolo, Edward Lyman, Mark S.P. Sansom, et al.. (2025). Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery. Nature Reviews Drug Discovery. 24(4). 251–275. 15 indexed citations
2.
Chen, Kuang-Yui Michael, Jason Lai, Jialu Wang, et al.. (2025). Computational design of highly signalling-active membrane receptors through solvent-mediated allosteric networks. Nature Chemistry. 17(3). 429–438. 1 indexed citations
3.
Skiba, Meredith A., Sarah M. Sterling, Shaun Rawson, et al.. (2024). Antibodies expand the scope of angiotensin receptor pharmacology. Nature Chemical Biology. 20(12). 1577–1585. 13 indexed citations
4.
Roberts, Jefferson, et al.. (2023). Computational design of dynamic receptor—peptide signaling complexes applied to chemotaxis. Nature Communications. 14(1). 2875–2875. 9 indexed citations
5.
Paradis, Justine S., Xiang Feng, Brigitte Murat, et al.. (2022). Computationally designed GPCR quaternary structures bias signaling pathway activation. Nature Communications. 13(1). 6826–6826. 17 indexed citations
6.
Schwengers, Oliver, Patrick Barth, Linda Falgenhauer, et al.. (2020). Platon: identification and characterization of bacterial plasmid contigs in short-read draft assemblies exploiting protein sequence-based replicon distribution scores. Microbial Genomics. 6(10). 131 indexed citations
7.
Yin, Jie, Kuang-Yui Michael Chen, Mary J. Clark, et al.. (2020). Structure of a D2 dopamine receptor–G-protein complex in a lipid membrane. Nature. 584(7819). 125–129. 139 indexed citations
8.
Chen, Kuang-Yui Michael, et al.. (2019). Computational design of G Protein-Coupled Receptor allosteric signal transductions. Nature Chemical Biology. 16(1). 77–86. 61 indexed citations
9.
Wang, Li, Kaifang Pang, Kihoon Han, et al.. (2019). An autism-linked missense mutation in SHANK3 reveals the modularity of Shank3 function. Molecular Psychiatry. 25(10). 2534–2555. 49 indexed citations
10.
Barth, Patrick, et al.. (2018). Reprogramming G protein coupled receptor structure and function. Current Opinion in Structural Biology. 51. 187–194. 20 indexed citations
11.
Feng, Xiang, et al.. (2017). Computational design of ligand-binding membrane receptors with high selectivity. Nature Chemical Biology. 13(7). 715–723. 28 indexed citations
12.
Feng, Xiang & Patrick Barth. (2016). A topological and conformational stability alphabet for multipass membrane proteins. Nature Chemical Biology. 12(3). 167–173. 24 indexed citations
13.
Barth, Patrick, et al.. (2015). Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy. Nature Communications. 6(1). 7196–7196. 30 indexed citations
14.
Swick, Michelle C., Patrick Barth, Minita Shah, et al.. (2013). Novel Conserved Genotypes Correspond to Antibiotic Resistance Phenotypes of E. coli Clinical Isolates. PLoS ONE. 8(6). e65961–e65961. 8 indexed citations
15.
Zhu, Jieqing, Bing Luo, Patrick Barth, et al.. (2009). The Structure of a Receptor with Two Associating Transmembrane Domains on the Cell Surface: Integrin αIIbβ3. Molecular Cell. 34(2). 234–249. 122 indexed citations
16.
Barth, Patrick, Jack Schonbrun, & David Baker. (2007). Toward high-resolution prediction and design of transmembrane helical protein structures. Proceedings of the National Academy of Sciences. 104(40). 15682–15687. 181 indexed citations
17.
Versele, Matthias, Vı́ctor J. Cid, Shirin Bahmanyar, et al.. (2004). Protein–Protein Interactions Governing Septin Heteropentamer Assembly and Septin Filament Organization inSaccharomyces cerevisiae. Molecular Biology of the Cell. 15(10). 4568–4583. 127 indexed citations
18.
Vollrath, Fritz, et al.. (2002). Local tolerance to spider silks and protein polymers in vivo.. PubMed. 16(4). 229–34. 76 indexed citations
19.
Calderone, V., Bernard Chevrier, M. Van Zandt, et al.. (2000). The structure of human aldose reductase bound to the inhibitor IDD384. Acta Crystallographica Section D Biological Crystallography. 56(5). 536–540. 33 indexed citations
20.
Rondeau, Jean‐Michel, et al.. (1987). Crystallization and preliminary X-ray study of pig lens aldose reductase. Journal of Molecular Biology. 195(4). 945–948. 11 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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