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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
21 Feb 2014-Science
TL;DR: In this article, 3D Dirac fermions with linear dispersions along all momentum directions were detected in 3D topological Dirac semimetals (TDSs) with angle-resolved photoemission spectroscopy.
Abstract: Three-dimensional (3D) topological Dirac semimetals (TDSs) represent an unusual state of quantum matter that can be viewed as “3D graphene.” In contrast to 2D Dirac fermions in graphene or on the surface of 3D topological insulators, TDSs possess 3D Dirac fermions in the bulk. By investigating the electronic structure of Na 3 Bi with angle-resolved photoemission spectroscopy, we detected 3D Dirac fermions with linear dispersions along all momentum directions. Furthermore, we demonstrated the robustness of 3D Dirac fermions in Na 3 Bi against in situ surface doping. Our results establish Na 3 Bi as a model system for 3D TDSs, which can serve as an ideal platform for the systematic study of quantum phase transitions between rich topological quantum states.

1,920 citations

Book ChapterDOI
Roy Harrod1
TL;DR: In this paper, a tentative and preliminary attempt to give the outline of a dynamic theory for change is made. But it has not yet been discussed in detail in detail, but a framework of concepts relevant to the study of change analogous to that provided by static theory is provided.
Abstract: 1. The following pages constitute a tentative and preliminary attempt to give the outline of a ‘dynamic’ theory. Static theory consists of a classification of terms with a view to systematic thinking, together with the extraction of such knowledge about the adjustments due to a change of circumstances as is yielded by the ‘laws of supply and demand’. It has for some time appeared to me that it ought to be possible to develop a similar classification and system of axioms to meet the situation in which certain forces are operating steadily to increase or decrease certain magnitudes in the system. The consequent ‘theory’ would not profess to determine the course of events in detail, but should provide a framework of concepts relevant to the study of change analogous to that provided by static theory for the study of rest.

1,920 citations

Journal ArticleDOI
TL;DR: MDAnalysis is an object‐oriented library for structural and temporal analysis of molecular dynamics simulation trajectories and individual protein structures that uses the powerful NumPy package to expose trajectory data as fast and efficient NumPy arrays.
Abstract: MDAnalysis is an object-oriented library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. It is written in the Python language with some performance-critical code in C. It uses the powerful NumPy package to expose trajectory data as fast and efficient NumPy arrays. It has been tested on systems of millions of particles. Many common file formats of simulation packages including CHARMM, Gromacs, Amber, and NAMD and the Protein Data Bank format can be read and written. Atoms can be selected with a syntax similar to CHARMM's powerful selection commands. MDAnalysis enables both novice and experienced programmers to rapidly write their own analytical tools and access data stored in trajectories in an easily accessible manner that facilitates interactive explorative analysis. MDAnalysis has been tested on and works for most Unix-based platforms such as Linux and Mac OS X. It is freely available under the GNU General Public License from http://mdanalysis.googlecode.com.

1,920 citations

Journal ArticleDOI
Dalila Pinto1, Alistair T. Pagnamenta2, Lambertus Klei3, Richard Anney4  +178 moreInstitutions (46)
15 Jul 2010-Nature
TL;DR: The genome-wide characteristics of rare (<1% frequency) copy number variation in ASD are analysed using dense genotyping arrays to reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
Abstract: The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

1,919 citations

Journal ArticleDOI
TL;DR: The following guidelines are excerpted (as permitted under the Creative Commons Attribution License (CCAL), with the knowledge and approval of PLoS Biology and the authors) from Kilkenny et al.
Abstract: The following guidelines are excerpted (as permitted under the Creative Commons Attribution License (CCAL), with the knowledge and approval of PLoS Biology and the authors) from Kilkenny et al (2010). ​ Table

1,916 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