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Richard Durbin

Researcher at University of Cambridge

Publications -  337
Citations -  247542

Richard Durbin is an academic researcher from University of Cambridge. The author has contributed to research in topics: Genome & Population. The author has an hindex of 125, co-authored 319 publications receiving 207192 citations. Previous affiliations of Richard Durbin include Wellcome Trust Sanger Institute & University of Manchester.

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A direct multi-generational estimate of the human mutation rate from autozygous segments seen in thousands of parentally related individuals

TL;DR: Exome sequences from 3,222 British-Pakistani individuals with high parental relatedness are used to estimate exome mutation rates, finding frequent recurrence of mutations at polymorphic CpG sites, and an increase in C to T mutations in the Pakistani population compared to Europeans, suggesting that mutational processes have evolved rapidly between human populations.
Posted ContentDOI

Removing reference bias and improving indel calling in ancient DNA data analysis by mapping to a sequence variation graph

TL;DR: It is demonstrated that aligning aDNA sequences to variation graphs allows recovering a higher fraction of non-reference variation and effectively mitigates the impact of reference bias in population genetics analyses using aDNA, while retaining mapping sensitivity.
Journal ArticleDOI

Genomix: a method for combining gene-finders' predictions, which uses evolutionary conservation of sequence and intron–exon structure

TL;DR: Genomix was used to combine predictions from four gene-finders for Caenorhabditis elegans, by selecting the predicted exons that are best conserved with C.briggsae and C.elegans by increasing the exon-level specificity and sensitivity compared to the best input gene-finder.
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WormBase: Annotating many nematode genomes.

TL;DR: WormBase's role of genome sequence annotation is described, describing how it annotate and integrate data from a growing collection of nematode species and strains, and the impact on annotation quality of large functional genomics projects such as modENCODE is discussed.