Simon Gravel
Assistant Professor, Department of Human Genetics
Investigator, Victor Phillip Dahdaleh Institute of Genomic Medicine
PhD - Physics, Cornell University, 2009.
Postdoctoral Fellowship, Physics Department, Universität zu Köln.
Postdoctoral Fellowship - Theoretical Physics, Kavli Institute, Santa Barbara.
Postdoctoral Fellowship, Genetics Department, Stanford University.
Simon Gravel obtained his BSc and MSc in Mathematics and Physics from the Université de Montréal and his PhD in Physics from Cornell University in 2009. His research in Genetics began during a short postdoc in the Physics department at the Universität zu Köln and the Kavli Institute for Theoretical Physics in Santa Barbara, and continued in the Genetics department at Stanford University. He joined the Department of Human Genetics at Ã山ǿ¼é and the Genome Quebec Innovation Centre in 2013.
Professor Gravel’s is interested in learning about biology and evolution through creative analysis of high-throughput biological data. His group develops mathematical and statistical methods that take advantage of diverse data sources to refine our understanding of fundamental parameters of human history and biology. His recent research has focused on how the history of diverse human populations affected patterns of genetic diversity and disease. His group made contributions about the origins of modern humans, the successive waves of migrations that led to the formations of contemporary populations in the Americas, as well as the identification of genetic predispositions for disease.
This research is largely data-driven, and it combines modeling at multiple levels: we first wish to understand the fundamental biology underpinning evolution, such as the processes of mutation, recombination, and selection. To understand human genomes, we also need to understand how recent and ancient human history affected patterns of genetic diversity: ancient population expansions, recent migrations, and marriage patterns all impact genomic diversity, and in many cases we can reconstruct these events through careful modelling. Finally, we need to understand the behavior of cutting edge technology involved in the latest datasets. Professor Gravel’s group has projects focusing on anthropology and history, technology development, biology, and medicine, and is always happy to explore new opportunities involving new technologies and creative mathematical modeling.
- Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC et al.. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries. Nature. 2022;612 (7938):E7. doi: . PubMed Ìý.
- Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC et al.. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature. 2022;611 (7934):115-123. doi: . PubMed  PubMed Central .
- Alenezi, WM, Milano, L, Fierheller, CT, Serruya, C, Revil, T, Oros, KK et al.. The Genetic and Molecular Analyses of RAD51CÌý²¹²Ô»åÌýRAD51D Identifies Rare Variants Implicated in Hereditary Ovarian Cancer from a Genetically Unique Population. Cancers (Basel). 2022;14 (9):. doi: . PubMed  PubMed Central .
- Moldoveanu, D, Ramsay, L, Lajoie, M, Anderson-Trocme, L, Lingrand, M, Berry, D et al.. Spatially mapping the immune landscape of melanoma using imaging mass cytometry. Sci Immunol. 2022;7 (70):eabi5072. doi: . PubMed Ìý.
- Baumdicker, F, Bisschop, G, Goldstein, D, Gower, G, Ragsdale, AP, Tsambos, G et al.. Efficient ancestry and mutation simulation with msprime 1.0. Genetics. 2022;220 (3):. doi: . PubMed  PubMed Central .
- Zabad, S, Ragsdale, AP, Sun, R, Li, Y, Gravel, S. Assumptions about frequency-dependent architectures of complex traits bias measures of functional enrichment. Genet Epidemiol. 2021;45 (6):621-632. doi: . PubMed Ìý.
- Spear, ML, Diaz-Papkovich, A, Ziv, E, Yracheta, JM, Gravel, S, Torgerson, DG et al.. Recent shifts in the genomic ancestry of Mexican Americans may alter the genetic architecture of biomedical traits. Elife. 2020;9 :. doi: . PubMed  PubMed Central .
- Diaz-Papkovich, A, Anderson-Trocmé, L, Gravel, S. A review of UMAP in population genetics. J Hum Genet. 2021;66 (1):85-91. doi: . PubMed  PubMed Central .
- Martin, AR, Gignoux, CR, Walters, RK, Wojcik, GL, Neale, BM, Gravel, S et al.. Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations. Am J Hum Genet. 2020;107 (4):788-789. doi: . PubMed  PubMed Central .
- Ragsdale, AP, Nelson, D, Gravel, S, Kelleher, J. Lessons Learned from Bugs in Models of Human History. Am J Hum Genet. 2020;107 (4):583-588. doi: . PubMed  PubMed Central .