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Institution

University of Oxford

EducationOxford, 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..


Papers
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Journal ArticleDOI
TL;DR: A series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release are described.
Abstract: Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.

2,045 citations

MonographDOI
13 Feb 2003
TL;DR: In this paper, the authors explore the role of politicians and the public in the process of land-use development megaprojects and suggest practical solutions drawing on theory and scientific evidence from the several hundred projects in twenty nations and five continents.
Abstract: Promoters of multi-billion dollar land-use development megaprojects systematically misinform parliaments, the public and the media in order to get them approved and built This book not only explores these issues, but suggests practical solutions drawing on theory and scientific evidence from the several hundred projects in twenty nations and five continents It is of interest to students, scholars, planners, economists, auditors, politicians and concerned citizens

2,044 citations

Journal ArticleDOI
Thomas J. Hudson1, Thomas J. Hudson2, Warwick Anderson3, Axel Aretz4  +270 moreInstitutions (92)
15 Apr 2010
TL;DR: Systematic studies of more than 25,000 cancer genomes will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

2,041 citations

Posted Content
TL;DR: This paper proposed a new methodology for multidimensional poverty measurement consisting of an identification method ρk that extends the traditional intersection and union approaches, and a class of poverty measures Mα.
Abstract: This paper proposes a new methodology for multidimensional poverty measurement consisting of an identification method ρk that extends the traditional intersection and union approaches, and a class of poverty measures Mα. Our identification step employs two forms of cutoff: one within each dimension to determine whether a person is deprived in that dimension, and a second across dimensions that identifies the poor by ‘counting’ the dimensions in which a person is deprived. The aggregation step employs the FGT measures, appropriately adjusted to account for multidimensionality. The axioms are presented as joint restrictions on identification and the measures, and the methodology satisfies a range of desirable properties including decomposability. The identification method is particularly well suited for use with ordinal data, as is the first of our measures, the adjusted headcount ratio. We present some dominance results and an interpretation of the adjusted headcount ratio as a measure of unfreedom. Examples from the US and Indonesia illustrate our methodology.

2,040 citations

01 Jan 2006
TL;DR: This report presents the results of the 2006 PASCAL Visual Object Classes Challenge (VOC2006).
Abstract: This report presents the results of the 2006 PASCAL Visual Object Classes Challenge (VOC2006). Details of the challenge, data, and evaluation are presented. Participants in the challenge submitted descriptions of their methods, and these have been included verbatim. This document should be considered preliminary, and subject to change.

2,034 citations


Authors

Showing all 101421 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Douglas G. Altman2531001680344
Salim Yusuf2311439252912
George Davey Smith2242540248373
Yi Chen2174342293080
David J. Hunter2131836207050
Nicholas J. Wareham2121657204896
Christopher J L Murray209754310329
Cyrus Cooper2041869206782
Mark J. Daly204763304452
David Miller2032573204840
Mark I. McCarthy2001028187898
Raymond J. Dolan196919138540
Frank E. Speizer193636135891
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023654
20222,554
202117,608
202017,299
201915,037
201813,726