Simon Gravel

32.7k total citations · 2 hit papers
40 papers, 3.4k citations indexed

About

Simon Gravel is a scholar working on Genetics, Molecular Biology and Sociology and Political Science. According to data from OpenAlex, Simon Gravel has authored 40 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Genetics, 4 papers in Molecular Biology and 3 papers in Sociology and Political Science. Recurrent topics in Simon Gravel's work include Genetic Associations and Epidemiology (27 papers), Genetic and phenotypic traits in livestock (13 papers) and Genetic diversity and population structure (11 papers). Simon Gravel is often cited by papers focused on Genetic Associations and Epidemiology (27 papers), Genetic and phenotypic traits in livestock (13 papers) and Genetic diversity and population structure (11 papers). Simon Gravel collaborates with scholars based in Canada, United States and France. Simon Gravel's co-authors include Carlos D. Bustamante, Eimear E. Kenny, Brian K. Maples, Christopher R. Gignoux, Aaron P. Ragsdale, Alicia R. Martin, Genevieve L. Wojcik, Mark J. Daly, Raymond K. Walters and Benjamin M. Neale and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Simon Gravel

37 papers receiving 3.3k citations

Hit Papers

Human Demographic History... 2017 2026 2020 2023 2017 2023 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simon Gravel Canada 22 2.5k 768 219 144 135 40 3.4k
Garrett Hellenthal United Kingdom 21 1.9k 0.8× 700 0.9× 246 1.1× 85 0.6× 146 1.1× 42 2.6k
Christopher R. Gignoux United States 27 2.3k 0.9× 749 1.0× 349 1.6× 148 1.0× 71 0.5× 74 3.8k
Daniel J. Lawson United Kingdom 21 2.0k 0.8× 764 1.0× 166 0.8× 64 0.4× 332 2.5× 59 3.1k
Sohini Ramachandran United States 21 2.7k 1.1× 886 1.2× 356 1.6× 102 0.7× 257 1.9× 46 4.3k
Agnar Helgason Iceland 34 2.7k 1.1× 1.4k 1.9× 336 1.5× 188 1.3× 159 1.2× 59 4.4k
Shuhua Xu China 31 2.1k 0.8× 1.2k 1.6× 348 1.6× 347 2.4× 90 0.7× 199 3.6k
Fernando Racimo United States 25 1.6k 0.6× 658 0.9× 342 1.6× 84 0.6× 235 1.7× 41 2.7k
Brenna M. Henn United States 31 2.0k 0.8× 710 0.9× 462 2.1× 68 0.5× 142 1.1× 68 3.4k
Jorge Rocha Portugal 25 1.1k 0.5× 601 0.8× 163 0.7× 192 1.3× 74 0.5× 78 2.8k
Neil Bradman United Kingdom 26 2.0k 0.8× 565 0.7× 297 1.4× 62 0.4× 54 0.4× 50 3.0k

Countries citing papers authored by Simon Gravel

Since Specialization
Citations

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

Fields of papers citing papers by Simon Gravel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Gravel

This figure shows the co-authorship network connecting the top 25 collaborators of Simon Gravel. A scholar is included among the top collaborators of Simon Gravel 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 Simon Gravel. Simon Gravel 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.
Zabad, Shadi, et al.. (2025). Toward whole-genome inference of polygenic scores with fast and memory-efficient algorithms. The American Journal of Human Genetics. 112(7). 1528–1546. 1 indexed citations
2.
Diaz-Papkovich, Alex, Guillaume Sillon, Daniela D’Agostino, et al.. (2025). Using the ancestral recombination graph to study the history of rare variants in founder populations. The American Journal of Human Genetics. 112(12). 2973–2981.
3.
Schurz, Haiko, Simon Gravel, Justin W. Myrick, et al.. (2025). The Indian Ocean slave trade and colonial expansion resulted in strong sex-biased admixture in South Africa. The American Journal of Human Genetics. 112(10). 2520–2537. 1 indexed citations
4.
Dupras, Charles, Marie‐Pierre Dubé, Simon Gravel, & Hazar Haidar. (2024). Accountability for Reasonableness as a Framework for the Promotion of Fair and Equitable Research. The Hastings Center Report. 54(S2). S66–S72. 1 indexed citations
5.
Anderson-Trocmé, Luke, Dominic Nelson, Shadi Zabad, et al.. (2023). On the genes, genealogies, and geographies of Quebec. Science. 380(6647). 849–855. 17 indexed citations
6.
Ragsdale, Aaron P., Timothy D. Weaver, Elizabeth G. Atkinson, et al.. (2023). A weakly structured stem for human origins in Africa. Nature. 617(7962). 755–763. 56 indexed citations breakdown →
7.
Spear, Melissa, Alex Diaz-Papkovich, Elad Ziv, et al.. (2020). Recent shifts in the genomic ancestry of Mexican Americans may alter the genetic architecture of biomedical traits. eLife. 9. 15 indexed citations
8.
Nelson, Dominic, Jerome Kelleher, Aaron P. Ragsdale, et al.. (2020). Accounting for long-range correlations in genome-wide simulations of large cohorts. PLoS Genetics. 16(5). e1008619–e1008619. 27 indexed citations
9.
Ragsdale, Aaron P., Dominic Nelson, Simon Gravel, & Jerome Kelleher. (2020). Lessons Learned from Bugs in Models of Human History. The American Journal of Human Genetics. 107(4). 583–588. 6 indexed citations
10.
Diaz-Papkovich, Alex, et al.. (2020). Don’t ignore genetic data from minority populations. Nature. 585(7824). 184–186. 34 indexed citations
11.
Ragsdale, Aaron P. & Simon Gravel. (2019). Unbiased Estimation of Linkage Disequilibrium from Unphased Data. Molecular Biology and Evolution. 37(3). 923–932. 22 indexed citations
12.
Anderson-Trocmé, Luke, Rick Farouni, Mathieu Bourgey, et al.. (2019). Legacy Data Confound Genomics Studies. Molecular Biology and Evolution. 37(1). 2–10. 17 indexed citations
13.
Ahmed, Zafarali, et al.. (2019). Learning proposals for sequential importance samplers using reinforced variational inference.. International Conference on Learning Representations.
14.
Ragsdale, Aaron P. & Simon Gravel. (2019). Models of archaic admixture and recent history from two-locus statistics. PLoS Genetics. 15(6). e1008204–e1008204. 51 indexed citations
15.
Diaz-Papkovich, Alex, et al.. (2019). UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts. PLoS Genetics. 15(11). e1008432–e1008432. 120 indexed citations
16.
Gravel, Simon, et al.. (2018). On the decidability of population size histories from finite allele frequency spectra. Theoretical Population Biology. 120. 42–51. 16 indexed citations
17.
Ragsdale, Aaron P., Claudia Moreau, & Simon Gravel. (2018). Genomic inference using diffusion models and the allele frequency spectrum. Current Opinion in Genetics & Development. 53. 140–147. 19 indexed citations
18.
Gravel, Simon. (2016). When Is Selection Effective?. Genetics. 203(1). 451–462. 52 indexed citations
19.
Gravel, Simon. (2014). Predicting Discovery Rates of Genomic Features. Genetics. 197(2). 601–610. 8 indexed citations
20.
Henn, Brenna M., Simon Gravel, Andrés Moreno‐Estrada, Suehelay Acevedo‐Acevedo, & Carlos D. Bustamante. (2010). Fine-scale population structure and the era of next-generation sequencing. Human Molecular Genetics. 19(R2). R221–R226. 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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