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| Nick Patterson | |
|---|---|
| Name | Nick Patterson |
| Fields | Computational biology; Statistical genetics; Bioinformatics |
| Workplaces | University of Cambridge; Broad Institute; Wellcome Sanger Institute |
| Alma mater | University of Cambridge; University of Oxford |
| Known for | Population genetics algorithms; Ancestry inference; STRUCTURE-like software; HMM methods |
Nick Patterson is a computational geneticist known for contributions to statistical methods in population genetics, genome analysis, and bioinformatics. He has worked at leading research institutions and collaborated on large-scale projects in human genetics, ancient DNA, and disease genomics. His work bridges algorithms, software engineering, and applied analysis, influencing studies involving human migration, admixture, and genomic variation.
Patterson trained in mathematics and computational sciences, studying at institutions associated with University of Cambridge and University of Oxford. During his formative years he engaged with research cultures connected to St John's College, Cambridge and interdisciplinary groups combining expertise from Wellcome Trust-funded programs and departments linked to European Molecular Biology Laboratory. His graduate and postdoctoral training integrated concepts from statistical inference developed in centers such as the Alan Turing Institute and methodology influenced by work at the Max Planck Institute for Evolutionary Anthropology.
Patterson's academic appointments include roles at the Wellcome Sanger Institute, the Broad Institute, and the University of Cambridge. At these institutions he collaborated with investigators affiliated with the University of Chicago, Harvard University, the Massachusetts Institute of Technology, and research consortia including the 1000 Genomes Project and the Human Genome Project. His research group developed methods applied in analyses of datasets generated by projects such as the Simons Genome Diversity Project and studies associated with the National Institutes of Health and European Research Council funded teams. Collaborators and coauthors have included scientists from the Max Planck Society, the Howard Hughes Medical Institute, and the Wellcome Trust Sanger Institute.
Patterson contributed to software and methodological toolkits used widely in population genetics, working alongside teams that produced pipelines used by researchers at the Natural History Museum, London and academic departments at the University of California, Berkeley. His work interfaced with laboratory-driven efforts in ancient DNA extraction at facilities exemplified by groups at the University of Copenhagen and computational efforts supported by cloud resources such as those used by the European Bioinformatics Institute.
Patterson is credited with developing and co-developing algorithms for ancestry inference, admixture detection, and haplotype-based analysis. He participated in producing tools and methods that have been used in high-profile studies of prehistoric human migrations analyzed in publications associated with teams from the Max Planck Institute for the Science of Human History and the University of Cambridge Department of Archaeology. Core methodological contributions include implementations of model-based clustering and likelihood-based tests that complement approaches from software like those produced by groups at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard.
His publications span journals and outlets that collaborate with editorial offices at institutions such as Nature Research, Science, and the Proceedings of the National Academy of Sciences; many studies were produced jointly with researchers from the University of Oxford and the University College London. Patterson coauthored influential papers on f-statistics, admixture graphs, and formal tests for population relationships that have been applied by teams working on the Denisova Cave findings, investigations involving specimens curated at the British Museum, and genomic surveys coordinated with the Wellcome Trust. His analytical frameworks have been cited by researchers at the University of Pennsylvania and in collaborative projects with groups from the Max Planck Institute for Evolutionary Anthropology.
Throughout his career Patterson has been recognized within the bioinformatics and genetics communities through invitations to present at conferences organized by societies such as the American Society of Human Genetics and the European Society of Human Genetics. His contributions earned him roles on advisory boards associated with initiatives at the National Human Genome Research Institute and within consortiums funded by agencies such as the Wellcome Trust and the European Commission. He has been acknowledged in prize committees and workshop programs convened by institutions like the Royal Society and the Gordon Research Conferences for population genomics and computational biology.
Patterson's work left an enduring imprint on methodological practice in population genetics, influencing how teams at archives like the Cambridge University Library and repositories at the European Molecular Biology Laboratory curate and analyze genomic data. His software and analytical paradigms continue to inform research projects at centers including the Broad Institute, the Wellcome Sanger Institute, and university laboratories at the University of Oxford and Harvard Medical School. Colleagues and trainees from institutions such as the University of Cambridge and the Max Planck Institute for Evolutionary Anthropology have propagated his approaches into studies of human prehistory, medical genetics, and conservation genomics, shaping ongoing collaborations across museums, research councils, and international consortia.
Category:Computational geneticists Category:Bioinformaticians Category:Population geneticists