Imperial College London


Faculty of Natural SciencesDepartment of Life Sciences (Silwood Park)

Lecturer in Quantitative Evolution



+44 (0)20 7594 3793m.fumagalli




N1.6MunroSilwood Park





The main focus of my research is population genetics, the study of genetic variation within species. The field is fundamental to understanding the genetic basis of adaptive traits, by elucidating the evolutionary forces that have shaped present-day genomic functional patterns. Population genomics approaches represent a valuable opportunity to address the evolutionary causes of modern complex diseases, by prioritising mutations for targeted association studies and functional experiments. I have developed and applied computational methods to highlight signatures of natural selection in the genome and to infer population demographic histories, by analysing large-scale datasets of model and non-model species. I have also designed and implemented software to analyse high-throughput sequencing data for evolutionary genomics purposes.



Torada L, Lorenzon L, Beddis A, et al., 2019, ImaGene: a convolutional neural network to quantify natural selection from genomic data, Bmc Bioinformatics, Vol:20, ISSN:1471-2105

Fox EA, Wright AE, Fumagalli M, et al., 2019, ngsLD: evaluating linkage disequilibrium using genotype likelihoods, Bioinformatics, Vol:35, ISSN:1367-4803, Pages:3855-3856

Fumagalli M, Camus SM, Diekmann Y, et al., 2019, Genetic diversity of CHC22 clathrin impacts its function in glucose metabolism, Elife, Vol:8, ISSN:2050-084X

Wright AE, Rogers TF, Fumagalli M, et al., 2019, Phenotypic sexual dimorphism is associated with genomic signatures of resolved sexual conflict, Molecular Ecology, Vol:28, ISSN:0962-1083, Pages:2860-2871


Adhikari K, Mendoza-Revilla J, Fumagalli M, et al., 2019, Genetic heterogeneity of pigmentation variation in Eurasia highlights independent evolution of lighter skin pigmentation, Annual Meeting of the British-Society-for-Investigative-Dermatology, WILEY, Pages:E201-E201, ISSN:0007-0963

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