Institution
University of Oxford
Education•Oxford, Oxfordshire, United Kingdom•
About: University of Oxford is a education organization based out in Oxford, Oxfordshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 99713 authors who have published 258108 publications receiving 12972806 citations. The organization is also known as: Oxford University & Oxon..
Topics: Population, Context (language use), Galaxy, Politics, Medicine
Papers published on a yearly basis
Papers
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University of Oxford1, University of Michigan2, Wellcome Trust Sanger Institute3, Amgen4, University of Cambridge5, University of Copenhagen6, University of Liverpool7, University of Freiburg8, Boston University9, University of Tartu10, Erasmus University Medical Center11, Leiden University Medical Center12, Pasteur Institute13, Icahn School of Medicine at Mount Sinai14, UCLA Medical Center15, Vanderbilt University Medical Center16, Wake Forest University17, National University of Singapore18, London North West Healthcare NHS Trust19, Imperial College London20, Charité21, Innsbruck Medical University22, Washington University in St. Louis23, Queen Mary University of London24, University of Southern Denmark25, National and Kapodistrian University of Athens26, Robertson Centre for Biostatistics27, University of Exeter28, Uppsala University29, University of Düsseldorf30, Steno Diabetes Center31, Aalborg University32, University of Eastern Finland33, Broad Institute34, Frederiksberg Hospital35, Lund University36, University of Bergen37, Technische Universität München38, University of North Carolina at Chapel Hill39, University of Edinburgh40, Ninewells Hospital41, University of Minnesota42, University of Glasgow43, Ludwig Maximilian University of Munich44, University of Iceland45, Aarhus University46, Science for Life Laboratory47, Stanford University48, University of Helsinki49, National Institutes of Health50, University of Dundee51, Harvard University52
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
1,136 citations
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TL;DR: This paper presents an efficient solution that explores the visual patterns within individual cropped regions with minimal costs, and builds the framework upon a representative one-stage keypoint-based detector named CornerNet, which improves both precision and recall.
Abstract: In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regions. This paper presents an efficient solution which explores the visual patterns within each cropped region with minimal costs. We build our framework upon a representative one-stage keypoint-based detector named CornerNet. Our approach, named CenterNet, detects each object as a triplet, rather than a pair, of keypoints, which improves both precision and recall. Accordingly, we design two customized modules named cascade corner pooling and center pooling, which play the roles of enriching information collected by both top-left and bottom-right corners and providing more recognizable information at the central regions, respectively. On the MS-COCO dataset, CenterNet achieves an AP of 47.0%, which outperforms all existing one-stage detectors by at least 4.9%. Meanwhile, with a faster inference speed, CenterNet demonstrates quite comparable performance to the top-ranked two-stage detectors. Code is available at this https URL.
1,136 citations
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TL;DR: A high-resolution genetic map of the human genome is presented, based on statistical analyses of genetic variation data, and more than 25,000 recombination hotspots are identified, together with motifs and sequence contexts that play a role in hotspot activity.
Abstract: Genetic maps, which document the way in which recombination rates vary over a genome, are an essential tool for many genetic analyses. We present a high-resolution genetic map of the human genome, based on statistical analyses of genetic variation data, and identify more than 25,000 recombination hotspots, together with motifs and sequence contexts that play a role in hotspot activity. Differences between the behavior of recombination rates over large (megabase) and small (kilobase) scales lead us to suggest a two-stage model for recombination in which hotspots are stochastic features, within a framework in which large-scale rates are constrained.
1,134 citations
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University of California, Berkeley1, University of Minnesota2, Queen Mary University of London3, Lawrence Berkeley National Laboratory4, California Institute of Technology5, Sapienza University of Rome6, Instituto Superior Técnico7, University of Oxford8, Cardiff University9, University of Toronto10
TL;DR: In this article, the authors presented a map and an angular power spectrum of the anisotropy of the cosmic microwave background (CMB) from the first flight of MAXIMA.
Abstract: We present a map and an angular power spectrum of the anisotropy of the cosmic microwave background (CMB) from the first flight of MAXIMA. MAXIMA is a balloon-borne experiment with an array of 16 bolometric photometers operated at 100 mK. MAXIMA observed a 124 deg region of the sky with 10' resolution at frequencies of 150, 240 and 410 GHz. The data were calibrated using in-flight measurements of the CMB dipole anisotropy. A map of the CMB anisotropy was produced from three 150 and one 240 GHz photometer without need for foreground subtractions. Analysis of this CMB map yields a power spectrum for the CMB anisotropy over the range 36 {le} {ell} {le} 785. The spectrum shows a peak with an amplitude of 78 {+-} 6 {mu}K at {ell} {approx_equal} 220 and an amplitude varying between {approx} 40 {mu}K and {approx} 50 {mu}K for 400 {approx}< {ell} {approx}< 785.
1,134 citations
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Broad Institute1, Harvard University2, Howard Hughes Medical Institute3, University of California, Berkeley4, University of California, Los Angeles5, Chinese Academy of Sciences6, Max Planck Society7, Columbia University8, Massachusetts Institute of Technology9, Cayetano Heredia University10, University of Pennsylvania11, University College London12, University of Bern13, Leiden University14, Nanyang Technological University15, University of Chicago16, Estonian Biocentre17, National University of La Plata18, University of Oxford19, University of Bergen20, Novosibirsk State University21, Moscow Institute of Physics and Technology22, Sofia Medical University23, Armenian National Academy of Sciences24, Wellcome Trust Sanger Institute25, Raja Isteri Pengiran Anak Saleha Hospital26, Case Western Reserve University27, University of Tartu28, Estonian Academy of Sciences29, Stony Brook University30, Illumina31, Gladstone Institutes32, University of Helsinki33, University of Washington34, Bashkir State University35, Jaramogi Oginga Odinga University of Science and Technology36, Pompeu Fabra University37, University of Arizona38, University of Cambridge39, Leidos40, Université de Montréal41, University of Utah42, Altai State University43, Council of Scientific and Industrial Research44
TL;DR: It is demonstrated that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
Abstract: Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.
1,133 citations
Authors
Showing all 101421 results
Name | H-index | Papers | Citations |
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Eric S. Lander | 301 | 826 | 525976 |
Albert Hofman | 267 | 2530 | 321405 |
Douglas G. Altman | 253 | 1001 | 680344 |
Salim Yusuf | 231 | 1439 | 252912 |
George Davey Smith | 224 | 2540 | 248373 |
Yi Chen | 217 | 4342 | 293080 |
David J. Hunter | 213 | 1836 | 207050 |
Nicholas J. Wareham | 212 | 1657 | 204896 |
Christopher J L Murray | 209 | 754 | 310329 |
Cyrus Cooper | 204 | 1869 | 206782 |
Mark J. Daly | 204 | 763 | 304452 |
David Miller | 203 | 2573 | 204840 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Raymond J. Dolan | 196 | 919 | 138540 |
Frank E. Speizer | 193 | 636 | 135891 |