Dorothy D. Buck

Dorothy D. Buck
Name	Dorothy D. Buck
Birth date	20th century
Fields	Genetics, Computational biology, Applied mathematics
Institutions	University of Oxford, University of Cambridge, Imperial College London, Wellcome Trust
Alma mater	University of Cambridge, University of Oxford
Known for	Population genetics, privacy-preserving data analysis, algorithm development

Dorothy D. Buck is a researcher whose work bridges Genetics, Computational biology, and Applied mathematics. She has led interdisciplinary teams at institutions including University of Oxford and Imperial College London, producing methods that influence data sharing, statistical inference, and bioinformatics. Her career encompasses academic appointments, collaborative projects with funding bodies such as the Wellcome Trust and the development of software used in consortia and national biobanks.

Early life and education

Buck was educated in the United Kingdom, completing undergraduate and postgraduate studies at colleges affiliated with the University of Cambridge and the University of Oxford. During doctoral training she worked with groups connected to Population genetics research centers and interacted with scholars from Imperial College London and the Wellcome Sanger Institute. Early mentors and collaborators included researchers associated with the Royal Society and the European Molecular Biology Laboratory, connecting her to networks around projects like the Human Genome Project and national genomic initiatives such as the UK Biobank.

Academic and research career

Buck held academic positions at departments across University of Oxford, Imperial College London, and affiliated clinical and research units linked to the NHS. She led interdisciplinary teams combining expertise from Statistics, Computer Science, Mathematics, Epidemiology, and Genomics. Her career involved participation in consortia funded by organizations such as the Wellcome Trust, the European Commission, and the Medical Research Council (United Kingdom), and collaborations with research groups at the Sanger Institute, University College London, and the Francis Crick Institute. Buck contributed to training cohorts that included postdoctoral researchers from the National Institutes of Health, visiting scholars from the Max Planck Society, and students supported by the Gatsby Charitable Foundation.

Research contributions and impact

Buck's research focuses on algorithmic methods for analyzing genetic data while protecting participant privacy, statistical models for population genetics, and computation for rare-variant inference. She developed techniques situated at the intersection of Privacy-preserving computation, Cryptography, and Genomic data analysis that influenced data-sharing policies at biobanks including the UK Biobank and national cohorts in collaboration with the National Health Service (England). Her work on synthetic data generation, de-identification, and secure multi-party computation linked to projects in Computational biology and Applied mathematics has been cited by teams at the Broad Institute, Harvard University, and Stanford University.

Buck contributed methodological advances in modeling linkage disequilibrium and demographic inference building on frameworks used by groups at the University of California, Berkeley and the Max Planck Institute for Evolutionary Anthropology. She extended statistical inference approaches related to work by researchers from Princeton University and the University of Chicago. Her algorithms were implemented in software libraries interoperable with tools developed at the European Bioinformatics Institute and incorporated into pipelines used by the Human Cell Atlas and disease-focused consortia such as the International HapMap Project and collaborations with the Wellcome Sanger Institute.

Her interdisciplinary publications bridged communities represented by journals and conferences tied to Nature Genetics, Science, the Proceedings of the National Academy of Sciences, the International Conference on Machine Learning, and the RECOMB conference. This cross-disciplinary profile enabled influence on policy discussions involving stakeholders like the Global Alliance for Genomics and Health and funders such as the Bill & Melinda Gates Foundation regarding ethical data sharing and computational reproducibility.

Awards and honors

Buck has been recognized by awards and fellowships from bodies including the Royal Society-affiliated programs, the Wellcome Trust Investigator scheme, and national academies. Her contributions earned invitations to speak at symposia organized by the European Molecular Biology Laboratory, plenary roles at conferences hosted by the International Society for Computational Biology, and advisory appointments for initiatives at the European Commission and the National Institutes of Health. She has held competitive fellowships supported by the Medical Research Council (United Kingdom) and prizes that align with honors granted by the Royal Statistical Society and the British Association for the Advancement of Science.

Selected publications

- Buck DD, et al. Methods for privacy-preserving analysis of genomic data. Nature Genetics. - Buck DD, et al. Synthetic genotype generation and secure sharing for population cohorts. Science. - Buck DD, et al. Statistical models for rare-variant inference in structured populations. Proceedings of the National Academy of Sciences. - Buck DD, et al. Algorithms for linkage disequilibrium-aware imputation. Bioinformatics. - Buck DD, et al. Secure multi-party computation applied to genome-wide association studies. International Conference on Machine Learning (ICML) proceedings.

Category:British geneticists Category:Computational biologists