Samuel Soubeyrand

2.7k total citations
96 papers, 1.7k citations indexed

About

Samuel Soubeyrand is a scholar working on Plant Science, Genetics and Ecology. According to data from OpenAlex, Samuel Soubeyrand has authored 96 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Plant Science, 22 papers in Genetics and 15 papers in Ecology. Recurrent topics in Samuel Soubeyrand's work include Wheat and Barley Genetics and Pathology (17 papers), Plant Virus Research Studies (11 papers) and Plant Pathogenic Bacteria Studies (10 papers). Samuel Soubeyrand is often cited by papers focused on Wheat and Barley Genetics and Pathology (17 papers), Plant Virus Research Studies (11 papers) and Plant Pathogenic Bacteria Studies (10 papers). Samuel Soubeyrand collaborates with scholars based in France, Morocco and Finland. Samuel Soubeyrand's co-authors include Lionel Roques, Cindy E. Morris, Gaël Thébaud, Anna‐Liisa Laine, Joël Chadœuf, Antti Penttinen, Daniel T. Haydon, E. K. Bigg, Etienne K. Klein and Emmanuel Jacquot and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Samuel Soubeyrand

91 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samuel Soubeyrand France 24 704 436 343 329 201 96 1.7k
Nik J. Cunniffe United Kingdom 29 1.7k 2.4× 237 0.5× 485 1.4× 299 0.9× 276 1.4× 79 2.5k
John E. Banks United States 23 981 1.4× 374 0.9× 1.4k 4.0× 560 1.7× 493 2.5× 76 2.8k
Marc Choisy France 27 217 0.3× 413 0.9× 152 0.4× 109 0.3× 322 1.6× 89 2.1k
Bret D. Elderd United States 20 156 0.2× 266 0.6× 289 0.8× 238 0.7× 374 1.9× 41 1.1k
João A. N. Filipe United Kingdom 20 410 0.6× 236 0.5× 114 0.3× 81 0.2× 354 1.8× 55 1.7k
Jemma L. Geoghegan New Zealand 25 326 0.5× 307 0.7× 88 0.3× 110 0.3× 319 1.6× 72 1.8k
Benjamin J. Ridenhour United States 22 173 0.2× 519 1.2× 115 0.3× 455 1.4× 336 1.7× 47 1.8k
Uno Wennergren Sweden 20 253 0.4× 164 0.4× 215 0.6× 393 1.2× 540 2.7× 55 1.5k
Lee W. Cohnstaedt United States 22 273 0.4× 129 0.3× 406 1.2× 390 1.2× 131 0.7× 104 1.5k
M. J. Jeger United Kingdom 35 3.1k 4.4× 387 0.9× 751 2.2× 479 1.5× 484 2.4× 97 3.9k

Countries citing papers authored by Samuel Soubeyrand

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Soubeyrand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Soubeyrand

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Soubeyrand. A scholar is included among the top collaborators of Samuel Soubeyrand 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 Samuel Soubeyrand. Samuel Soubeyrand 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.
Gabriel, Edith, et al.. (2025). A marked sequential point process for disease surveillance: Modeling and optimization. Spatial Statistics. 68. 100913–100913.
2.
Coville, Jérôme, Constance Xhaard, Pascal Frey, et al.. (2024). A mechanistic-statistical approach to infer dispersal and demography from invasion dynamics, applied to a plant pathogen. SHILAP Revista de lepidopterología. 4. 2 indexed citations
3.
Goyeau, Henriette, et al.. (2023). A landscape-scale field survey demonstrates the role of wheat volunteers as a local and diversified source of leaf rust inoculum. Scientific Reports. 13(1). 20411–20411. 2 indexed citations
4.
5.
Coville, Jérôme, et al.. (2020). Equilibrium and sensitivity analysis of a spatio-temporal host-vector epidemic model. Nonlinear Analysis Real World Applications. 57. 103194–103194. 3 indexed citations
6.
Roques, Lionel, et al.. (2020). Impact of Lockdown on the Epidemic Dynamics of COVID-19 in France. Frontiers in Medicine. 7. 274–274. 45 indexed citations
7.
Roques, Lionel, et al.. (2020). A parsimonious approach for spatial transmission and heterogeneity in the COVID-19 propagation. Royal Society Open Science. 7(12). 201382–201382. 23 indexed citations
8.
Rimbaud, Loup, Sylvie Dallot, Sophie Thoyer, et al.. (2019). Improving Management Strategies of Plant Diseases Using Sequential Sensitivity Analyses. Phytopathology. 109(7). 1184–1197. 14 indexed citations
9.
Soubeyrand, Samuel, et al.. (2019). Analyzing the Influence of Landscape Aggregation on Disease Spread to Improve Management Strategies. Phytopathology. 109(7). 1198–1207. 7 indexed citations
10.
Soubeyrand, Samuel, Caroline Monteil, Frédéric Suffert, et al.. (2017). Testing Differences Between Pathogen Compositions with Small Samples and Sparse Data. Phytopathology. 107(10). 1199–1208. 5 indexed citations
11.
Walker, Emily, et al.. (2017). Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms. The Science of The Total Environment. 624. 470–479. 10 indexed citations
12.
Dallot, Sylvie, Kirstyn Brunker, Karine Berthier, et al.. (2017). Exploiting Genetic Information to Trace Plant Virus Dispersal in Landscapes. Annual Review of Phytopathology. 55(1). 139–160. 14 indexed citations
13.
Bigg, E. K., Samuel Soubeyrand, & Cindy E. Morris. (2015). Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause. Atmospheric chemistry and physics. 15(5). 2313–2326. 50 indexed citations
14.
Rimbaud, Loup, et al.. (2015). Assessing the Mismatch Between Incubation and Latent Periods for Vector-Borne Diseases: The Case of Sharka. Phytopathology. 105(11). 1408–1416. 18 indexed citations
15.
Bigg, E. K., Samuel Soubeyrand, & Cindy E. Morris. (2014). Rainfall feedback via persistent effects on bioaerosols. 1 indexed citations
16.
Roques, Lionel, Mickaël D. Chekroun, Michel Cristofol, Samuel Soubeyrand, & Michael Ghil. (2014). Parameter estimation for energy balance models with memory. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 470(2169). 20140349–20140349. 23 indexed citations
17.
Dussaubat, Claudia, Alban Maisonnasse, Didier Crauser, et al.. (2013). Flight behavior and pheromone changes associated to Nosema ceranae infection of honey bee workers (Apis mellifera) in field conditions. Journal of Invertebrate Pathology. 113(1). 42–51. 114 indexed citations
18.
Morelli, Marco J., Gaël Thébaud, Joël Chadœuf, et al.. (2012). A Bayesian Inference Framework to Reconstruct Transmission Trees Using Epidemiological and Genetic Data. PLoS Computational Biology. 8(11). e1002768–e1002768. 89 indexed citations
19.
Lannou, Christian, Samuel Soubeyrand, Lise Frézal, & Joël Chadœuf. (2008). Autoinfection in wheat leaf rust epidemics. New Phytologist. 177(4). 1001–1011. 28 indexed citations
20.
Soubeyrand, Samuel, Jérôme Enjalbert, & Ivan Sache. (2007). Accounting for roughness of circular processes: Using Gaussian random processes to model the anisotropic spread of airborne plant disease. Theoretical Population Biology. 73(1). 92–103. 25 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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