Shamil Sunyaev

Shamil Sunyaev, PhD

Professor of Biomedical Informatics, Harvard Medical School
Professor of Medicine, Brigham and Women’s Hospital

10 Shattuck Street, Room 311A, Boston, MA 02115

Shamil Sunyaev is a computational genomicist and geneticist. Research in his lab encompasses many aspects of population genetic variation including the origin of mutations, the effect of allelic variants on molecular function, population and evolutionary genetics, and genetics of human complex and Mendelian traits. He developed several computational and statistical methods widely adopted by the community. Sunyaev obtained a PhD in molecular biophysics from the Moscow Institute of Physics and Technology and completed his postdoctoral training in bioinformatics at the European Molecular Biology Laboratory (EMBL). He is an Institute Member at Broad Institute of MIT and Harvard. He also co-organizes the Boston Evolutionary Genomics Supergroup.


DBMI Research Areas
DBMI Courses
Population-specific causal disease effect sizes in functionally important regions impacted by selection.
Authors: Shi H, Gazal S, Kanai M, Koch EM, Schoech AP, Siewert KM, Kim SS, Luo Y, Amariuta T, Huang H, Okada Y, Raychaudhuri S, Sunyaev SR, Price AL.
Nat Commun
View full abstract on Pubmed
Polygenic adaptation of rosette growth in Arabidopsis thaliana.
Authors: Wieters B, Steige KA, He F, Koch EM, Ramos-Onsins SE, Gu H, Guo YL, Sunyaev S, de Meaux J.
PLoS Genet
View full abstract on Pubmed
Maintenance of Complex Trait Variation: Classic Theory and Modern Data.
Authors: Koch EM, Sunyaev SR.
Front Genet
View full abstract on Pubmed
Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.
Authors: Kousi M, Söylemez O, Ozanturk A, Mourtzi N, Akle S, Jungreis I, Muller J, Cassa CA, Brand H, Mokry JA, Wolf MY, Sadeghpour A, McFadden K, Lewis RA, Talkowski ME, Dollfus H, Kellis M, Davis EE, Sunyaev SR, Katsanis N.
Nat Genet
View full abstract on Pubmed
Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.
Authors: Li X, Li Z, Zhou H, Gaynor SM, Liu Y, Chen H, Sun R, Dey R, Arnett DK, Aslibekyan S, Ballantyne CM, Bielak LF, Blangero J, Boerwinkle E, Bowden DW, Broome JG, Conomos MP, Correa A, Cupples LA, Curran JE, Freedman BI, Guo X, Hindy G, Irvin MR, Kardia SLR, Kathiresan S, Khan AT, Kooperberg CL, Laurie CC, Liu XS, Mahaney MC, Manichaikul AW, Martin LW, Mathias RA, McGarvey ST, Mitchell BD, Montasser ME, Moore JE, Morrison AC, O'Connell JR, Palmer ND, Pampana A, Peralta JM, Peyser PA, Psaty BM, Redline S, Rice KM, Rich SS, Smith JA, Tiwari HK, Tsai MY, Vasan RS, Wang FF, Weeks DE, Weng Z, Wilson JG, Yanek LR, Neale BM, Sunyaev SR, Abecasis GR, Rotter JI, Willer CJ, Peloso GM, Natarajan P, Lin X.
Nat Genet
View full abstract on Pubmed
Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.
Authors: Chun S, Imakaev M, Hui D, Patsopoulos NA, Neale BM, Kathiresan S, Stitziel NO, Sunyaev SR.
Am J Hum Genet
View full abstract on Pubmed
Identification of cancer driver genes based on nucleotide context.
Authors: Dietlein F, Weghorn D, Taylor-Weiner A, Richters A, Reardon B, Liu D, Lander ES, Van Allen EM, Sunyaev SR.
Nat Genet
View full abstract on Pubmed
Fine-Scale Haplotype Structure Reveals Strong Signatures of Positive Selection in a Recombining Bacterial Pathogen.
Authors: Arnold B, Sohail M, Wadsworth C, Corander J, Hanage WP, Sunyaev S, Grad YH.
Mol Biol Evol
View full abstract on Pubmed
Mutations in RABL3 alter KRAS prenylation and are associated with hereditary pancreatic cancer.
Authors: Nissim S, Leshchiner I, Mancias JD, Greenblatt MB, Maertens O, Cassa CA, Rosenfeld JA, Cox AG, Hedgepeth J, Wucherpfennig JI, Kim AJ, Henderson JE, Gonyo P, Brandt A, Lorimer E, Unger B, Prokop JW, Heidel JR, Wang XX, Ukaegbu CI, Jennings BC, Paulo JA, Gableske S, Fierke CA, Getz G, Sunyaev SR, Wade Harper J, Cichowski K, Kimmelman AC, Houvras Y, Syngal S, Williams C, Goessling W.
Nat Genet
View full abstract on Pubmed
GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions.
Authors: Farhat MR, Freschi L, Calderon R, Ioerger T, Snyder M, Meehan CJ, de Jong B, Rigouts L, Sloutsky A, Kaur D, Sunyaev S, van Soolingen D, Shendure J, Sacchettini J, Murray M.
Nat Commun
View full abstract on Pubmed