Rémi Monasson

6.5k total citations
119 papers, 3.5k citations indexed

About

Rémi Monasson is a scholar working on Molecular Biology, Cognitive Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Rémi Monasson has authored 119 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 27 papers in Cognitive Neuroscience and 24 papers in Statistical and Nonlinear Physics. Recurrent topics in Rémi Monasson's work include Neural dynamics and brain function (24 papers), Theoretical and Computational Physics (22 papers) and Protein Structure and Dynamics (19 papers). Rémi Monasson is often cited by papers focused on Neural dynamics and brain function (24 papers), Theoretical and Computational Physics (22 papers) and Protein Structure and Dynamics (19 papers). Rémi Monasson collaborates with scholars based in France, United States and Italy. Rémi Monasson's co-authors include Simona Cocco, Riccardo Zecchina, John F. Marko, Scott Kirkpatrick, Bart Selman, Martin Weigt, Stanislas Leibler, Jérôme Tubiana, Mikhail Tikhonov and Olivier Martin and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Rémi Monasson

113 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rémi Monasson France 30 1.2k 703 661 585 505 119 3.5k
Martin Weigt France 36 3.9k 3.2× 587 0.8× 577 0.9× 917 1.6× 488 1.0× 103 6.1k
Riccardo Zecchina Italy 39 2.9k 2.3× 831 1.2× 1.7k 2.6× 1.2k 2.0× 1.6k 3.1× 128 7.2k
Christopher R. Myers United States 30 1.8k 1.5× 402 0.6× 274 0.4× 510 0.9× 207 0.4× 81 4.9k
Lenka Zdeborová France 27 356 0.3× 617 0.9× 1.6k 2.5× 1.9k 3.2× 694 1.4× 104 5.0k
Thierry Mora France 38 2.0k 1.6× 406 0.6× 267 0.4× 695 1.2× 400 0.8× 129 5.3k
Ido Kanter Israel 38 422 0.3× 535 0.8× 2.0k 3.1× 1.7k 2.9× 1.6k 3.2× 192 4.9k
Olivier Martin France 43 2.4k 1.9× 950 1.4× 494 0.7× 558 1.0× 359 0.7× 196 6.5k
Florent Krząkała France 32 240 0.2× 993 1.4× 1.4k 2.1× 1.4k 2.4× 580 1.1× 114 4.0k
Zoltán Toroczkai United States 35 460 0.4× 535 0.8× 432 0.7× 1.9k 3.2× 733 1.5× 96 5.7k
Ernesto P. Raposo Brazil 35 2.5k 2.1× 503 0.7× 452 0.7× 713 1.2× 249 0.5× 130 5.1k

Countries citing papers authored by Rémi Monasson

Since Specialization
Citations

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

Fields of papers citing papers by Rémi Monasson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rémi Monasson

This figure shows the co-authorship network connecting the top 25 collaborators of Rémi Monasson. A scholar is included among the top collaborators of Rémi Monasson 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 Rémi Monasson. Rémi Monasson 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.
Fernández-de-Cossio-Díaz, Jorge, Pierre Hardouin, Yann Ponty, et al.. (2025). Designing molecular RNA switches with Restricted Boltzmann machines. Nature Communications. 16(1). 11223–11223.
2.
Rehan, Ahmed, et al.. (2025). Design and experimental characterization of specificity-switching mutational paths of WW domains. bioRxiv (Cold Spring Harbor Laboratory).
3.
Cocco, Simona, Lorenzo Posani, & Rémi Monasson. (2024). Functional effects of mutations in proteins can be predicted and interpreted by guided selection of sequence covariation information. Proceedings of the National Academy of Sciences. 121(26). e2312335121–e2312335121. 4 indexed citations
4.
Fernández-de-Cossio-Díaz, Jorge, Simona Cocco, & Rémi Monasson. (2023). Disentangling Representations in Restricted Boltzmann Machines without Adversaries. Physical Review X. 13(2). 9 indexed citations
5.
Bravi, Barbara, Jorge Fernández-de-Cossio-Díaz, Aleksandra M. Walczak, et al.. (2023). A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity. eLife. 12. 12 indexed citations
6.
Depardieu, Florence, et al.. (2023). Computational design of novel Cas9 PAM-interacting domains using evolution-based modelling and structural quality assessment. PLoS Computational Biology. 19(11). e1011621–e1011621. 9 indexed citations
7.
Cocco, Simona, et al.. (2022). Optimal regularizations for data generation with probabilistic graphical models. Journal of Statistical Mechanics Theory and Experiment. 2022(5). 53502–53502. 2 indexed citations
8.
Šulc, Petr, et al.. (2021). The Heterogeneous Landscape and Early Evolution of Pathogen-Associated CpG Dinucleotides in SARS-CoV-2. Molecular Biology and Evolution. 38(6). 2428–2445. 13 indexed citations
9.
Bikard, David, et al.. (2021). Improving sequence-based modeling of protein families using secondary-structure quality assessment. Bioinformatics. 37(22). 4083–4090. 5 indexed citations
10.
Russ, William P., Matteo Figliuzzi, Christian Stocker, et al.. (2020). An evolution-based model for designing chorismate mutase enzymes. Science. 369(6502). 440–445. 166 indexed citations
11.
Coucke, Alice, et al.. (2020). Inference of compressed Potts graphical models. Physical review. E. 101(1). 12309–12309. 14 indexed citations
12.
Dubreuil, Alexis, et al.. (2019). Can Grid Cell Ensembles Represent Multiple Spaces?. Neural Computation. 31(12). 2324–2347. 13 indexed citations
13.
Jacquin, Hugo, et al.. (2016). Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models. PLoS Computational Biology. 12(5). e1004889–e1004889. 39 indexed citations
14.
Cocco, Simona, John F. Marko, & Rémi Monasson. (2014). Stochastic Ratchet Mechanisms for Replacement of Proteins Bound to DNA. Physical Review Letters. 112(23). 238101–238101. 21 indexed citations
15.
Cocco, Simona & Rémi Monasson. (2011). Adaptive Cluster Expansion for Inferring Boltzmann Machines with Noisy Data. Physical Review Letters. 106(9). 90601–90601. 90 indexed citations
16.
théorique, École d'été de physique, D. Chatenay, Simona Cocco, et al.. (2005). Multiple aspects of DNA and RNA : from biophysics to bioinformatics : École d'été de physique des Houches, session LXXXII, 2-27 August 2004, Euro Summer School, NATO Advanced Study Institute, École thématique du CNRS. Elsevier eBooks. 1 indexed citations
17.
Cocco, Simona, Rémi Monasson, & John F. Marko. (2002). Unzipping dynamics of long DNAs. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 66(5). 51914–51914. 20 indexed citations
18.
Martin, Olivier, Rémi Monasson, & Riccardo Zecchina. (2001). Statistical mechanics methods and phase transitions in optimization problems. Theoretical Computer Science. 265(1-2). 3–67. 91 indexed citations
19.
Cocco, Simona & Rémi Monasson. (2001). Trajectories in Phase Diagrams, Growth Processes, and Computational Complexity: How Search Algorithms Solve the 3-Satisfiability Problem. Physical Review Letters. 86(8). 1654–1657. 42 indexed citations
20.
Monasson, Rémi, et al.. (1996). Phase Transition and Search Cost in the 2+p-SAT Problem. PORTO Publications Open Repository TOrino (Politecnico di Torino). 20 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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