Richard Bonneau

36.7k total citations · 15 hit papers
243 papers, 19.1k citations indexed

About

Richard Bonneau is a scholar working on Molecular Biology, Communication and Sociology and Political Science. According to data from OpenAlex, Richard Bonneau has authored 243 papers receiving a total of 19.1k indexed citations (citations by other indexed papers that have themselves been cited), including 155 papers in Molecular Biology, 28 papers in Communication and 28 papers in Sociology and Political Science. Recurrent topics in Richard Bonneau's work include Protein Structure and Dynamics (35 papers), Bioinformatics and Genomic Networks (30 papers) and Social Media and Politics (28 papers). Richard Bonneau is often cited by papers focused on Protein Structure and Dynamics (35 papers), Bioinformatics and Genomic Networks (30 papers) and Social Media and Politics (28 papers). Richard Bonneau collaborates with scholars based in United States, Germany and United Kingdom. Richard Bonneau's co-authors include Joshua A. Tucker, Jonathan Nagler, David Baker, John T. Jost, Dan R. Littman, Pablo Barberá, Emily R. Miraldi, Zachary Kurtz, Christian L. Müller and Martin J. Blaser and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Richard Bonneau

239 papers receiving 18.8k citations

Hit Papers

Sparse and Compositionally Robust Inference of Microbial ... 2010 2026 2015 2020 2015 2017 2012 2015 2019 250 500 750 1000

Peers

Richard Bonneau
Michael Stern United States
Jumin Lee United States
Ron Milo Israel
Patrick R. Griffin United States
Susan R. Jones United Kingdom
Stanley Cohen United States
Ravi Dhar United States
Robert F. Murphy United States
Michael Stern United States
Richard Bonneau
Citations per year, relative to Richard Bonneau Richard Bonneau (= 1×) peers Michael Stern

Countries citing papers authored by Richard Bonneau

Since Specialization
Citations

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

Fields of papers citing papers by Richard Bonneau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Bonneau

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Bonneau. A scholar is included among the top collaborators of Richard Bonneau 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 Richard Bonneau. Richard Bonneau 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.
Dreyer, Frédéric A., Jan Ludwiczak, Brennan Abanades, et al.. (2025). Conformation-aware structure prediction of antigen-recognizing immune proteins. mAbs. 18(1). 2602217–2602217.
2.
Morton, James T., et al.. (2024). Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases. mSystems. 9(8). e0029524–e0029524. 7 indexed citations
3.
Otto, Tamara C., et al.. (2024). Computational Design of Phosphotriesterase Improves V‐Agent Degradation Efficiency. ChemistryOpen. 13(7). e202300263–e202300263. 4 indexed citations
4.
Jackson, Christopher A., Giuseppe-Antonio Saldi, Andreas Tjärnberg, et al.. (2022). High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0. Bioinformatics. 38(9). 2519–2528. 37 indexed citations
5.
Yi, Ren, Kyunghyun Cho, & Richard Bonneau. (2022). NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site prediction. Bioinformatics. 38(20). 4762–4770. 1 indexed citations
6.
Mahmoudinobar, Farbod, et al.. (2022). Tuning a coiled-coil hydrogel via computational design of supramolecular fiber assembly. Molecular Systems Design & Engineering. 8(2). 217–226. 8 indexed citations
7.
Geras, Krzysztof J., et al.. (2021). A convolutional neural network for common coordinate registration of high-resolution histology images. Bioinformatics. 37(22). 4216–4226. 7 indexed citations
8.
Barot, Meet, Vladimir Gligorijević, Kyunghyun Cho, & Richard Bonneau. (2021). NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarity. Bioinformatics. 37(16). 2414–2422. 14 indexed citations
9.
Favuzzi, Emilia, Shuhan Huang, Giuseppe-Antonio Saldi, et al.. (2021). GABA-receptive microglia selectively sculpt developing inhibitory circuits. Cell. 184(15). 4048–4063.e32. 193 indexed citations breakdown →
10.
Arrieta‐Ortiz, Mario L., et al.. (2020). Inference of Bacterial Small RNA Regulatory Networks and Integration with Transcription Factor-Driven Regulatory Networks. mSystems. 5(3). 11 indexed citations
11.
Gabitto, Mariano I., Orly L. Wapinski, Kathryn Allaway, et al.. (2020). Characterizing chromatin landscape from aggregate and single-cell genomic assays using flexible duration modeling. Nature Communications. 11(1). 747–747. 7 indexed citations
12.
Maniatis, Silas, Tarmo Äijö, Sanja Vicković, et al.. (2019). Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis. Science. 364(6435). 89–93. 276 indexed citations breakdown →
13.
Gligorijević, Vladimir, Meet Barot, & Richard Bonneau. (2018). deepNF: deep network fusion for protein function prediction. Bioinformatics. 34(22). 3873–3881. 151 indexed citations
14.
Koo, Da Chen Emily & Richard Bonneau. (2018). Towards region-specific propagation of protein functions. Bioinformatics. 35(10). 1737–1744. 8 indexed citations
15.
Äijö, Tarmo, Christian L. Müller, & Richard Bonneau. (2017). Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing. Bioinformatics. 34(3). 372–380. 42 indexed citations
16.
Renfrew, P. Douglas, et al.. (2017). Impact of phenylalanines outside the dimer interface on phosphotriesterase stability and function. Molecular BioSystems. 13(10). 2092–2106. 5 indexed citations
17.
Alford, Rebecca F., Andrew Leaver‐Fay, Jeliazko R. Jeliazkov, et al.. (2017). The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design. Journal of Chemical Theory and Computation. 13(6). 3031–3048. 942 indexed citations breakdown →
18.
Ruiz, Victoria, Thomas Battaglia, Zachary Kurtz, et al.. (2017). A single early-in-life macrolide course has lasting effects on murine microbial network topology and immunity. Nature Communications. 8(1). 518–518. 102 indexed citations
19.
Poultney, Christopher S., et al.. (2014). One third of dynamic protein expression profiles can be predicted by a simple rate equation. Molecular BioSystems. 10(11). 2850–2862. 19 indexed citations
20.
Miao, Edward A., Dat P. Mao, Natalya Yudkovsky, et al.. (2010). Innate immune detection of the type III secretion apparatus through the NLRC4 inflammasome. Proceedings of the National Academy of Sciences. 107(7). 3076–3080. 629 indexed citations breakdown →

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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