Institution
University of York
Education•York, York, United Kingdom•
About: University of York is a education organization based out in York, York, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 22089 authors who have published 56925 publications receiving 2458285 citations. The organization is also known as: York University & Ebor..
Topics: Population, Health care, Context (language use), Randomized controlled trial, Cost effectiveness
Papers published on a yearly basis
Papers
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TL;DR: Calcium Signals are identified as a central Paradigm in Stimulus–Response Coupling and are normally composed of elements that include calcium and Na6(SO4)2, Na2SO4, and Na2CO3.
Abstract: ### Calcium Signals: A Central Paradigm in Stimulus–Response Coupling
Cells must respond to an array of environmental and developmental cues. The signaling networks that have evolved to generate appropriate cellular responses are varied and are normally composed of elements that include a
1,156 citations
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1,156 citations
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TL;DR: This evolving classification rationalises structural and mechanistic investigation, harnesses information from a wide variety of related enzymes to inform cell biology and overcomes recurrent problems in the functional prediction of glycosyltransferase-related open-reading frames.
1,155 citations
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TL;DR: It is shown that the coevolutionary dynamic can be envisaged as a directed random walk in the community's trait space and a quantitative description of this stochastic process in terms of a master equation is derived.
Abstract: In this paper we develop a dynamical theory of coevolution in ecological communities. The derivation explicitly accounts for the stochastic components of evolutionary change and is based on ecological processes at the level of the individual. We show that the coevolutionary dynamic can be envisaged as a directed random walk in the community's trait space. A quantitative description of this stochastic process in terms of a master equation is derived. By determining the first jump moment of this process we abstract the dynamic of the mean evolutionary path. To first order the resulting equation coincides with a dynamic that has frequently been assumed in evolutionary game theory. Apart from recovering this canonical equation we systematically establish the underlying assumptions. We provide higher order corrections and show that these can give rise to new, unexpected evolutionary effects including shifting evolutionary isoclines and evolutionary slowing down of mean paths as they approach evolutionary equilibria. Extensions of the derivation to more general ecological settings are discussed. In particular we allow for multi-trait coevolution and analyze coevolution under nonequilibrium population dynamics.
1,147 citations
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Ghent University1, Forschungszentrum Jülich2, Åbo Akademi University3, Aalto University4, Vienna University of Technology5, Duke University6, University of Grenoble7, École Polytechnique Fédérale de Lausanne8, Durham University9, International School for Advanced Studies10, Max Planck Society11, Uppsala University12, Humboldt University of Berlin13, Fritz Haber Institute of the Max Planck Society14, Technical University of Denmark15, National Institute of Standards and Technology16, University of Udine17, Université catholique de Louvain18, University of Basel19, Harvard University20, University of California, Davis21, Rutgers University22, University of York23, Wake Forest University24, Science and Technology Facilities Council25, University of Oxford26, University of Vienna27, Dresden University of Technology28, Leibniz Institute for Neurobiology29, Radboud University Nijmegen30, University of Tokyo31, Centre national de la recherche scientifique32, University of Cambridge33, Royal Holloway, University of London34, University of California, Santa Barbara35, University of Luxembourg36, Los Alamos National Laboratory37, Harbin Institute of Technology38
TL;DR: A procedure to assess the precision of DFT methods was devised and used to demonstrate reproducibility among many of the most widely used DFT codes, demonstrating that the precisionof DFT implementations can be determined, even in the absence of one absolute reference code.
Abstract: The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.
1,141 citations
Authors
Showing all 22432 results
Name | H-index | Papers | Citations |
---|---|---|---|
Cyrus Cooper | 204 | 1869 | 206782 |
Eric R. Kandel | 184 | 603 | 113560 |
Ian J. Deary | 166 | 1795 | 114161 |
Elio Riboli | 158 | 1136 | 110499 |
Claude Bouchard | 153 | 1076 | 115307 |
Robert Plomin | 151 | 1104 | 88588 |
Kevin J. Gaston | 150 | 750 | 85635 |
John R. Hodges | 149 | 812 | 82709 |
Myrna M. Weissman | 149 | 772 | 108259 |
Jeffrey A. Lieberman | 145 | 706 | 85306 |
Howard L. Weiner | 144 | 1047 | 91424 |
Dan J. Stein | 142 | 1727 | 132718 |
Jedd D. Wolchok | 140 | 713 | 123336 |
Bernard Henrissat | 139 | 593 | 100002 |
Joseph E. LeDoux | 139 | 478 | 91500 |