Institution
University of Kent
Education•Canterbury, Kent, United Kingdom•
About: University of Kent is a education organization based out in Canterbury, Kent, United Kingdom. It is known for research contribution in the topics: Population & Poison control. The organization has 9627 authors who have published 28329 publications receiving 811712 citations. The organization is also known as: University of Kent at Canterbury & Cantuar..
Topics: Population, Poison control, Optical coherence tomography, Antenna (radio), Context (language use)
Papers published on a yearly basis
Papers
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TL;DR: The basics of the suject are looked at, a brief review of the theory is given, examining the strengths and weaknesses of its implementation, and some of the ways simulators approach problems are illustrated through a small case study.
Abstract: First-principles simulation, meaning density-functional theory calculations with plane waves and pseudopotentials, has become a prized technique in condensed-matter theory. Here I look at the basics of the suject, give a brief review of the theory, examining the strengths and weaknesses of its implementation, and illustrating some of the ways simulators approach problems through a small case study. I also discuss why and how modern software design methods have been used in writing a completely new modular version of the CASTEP code.
8,251 citations
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TL;DR: An updated protocol for Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants for a user's protein sequence.
Abstract: Phyre2 is a web-based tool for predicting and analyzing protein structure and function. Phyre2 uses advanced remote homology detection methods to build 3D models, predict ligand binding sites, and analyze amino acid variants in a protein sequence. Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2
. A typical structure prediction will be returned between 30 min and 2 h after submission.
6,204 citations
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5,218 citations
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TL;DR: Some of the research challenges in understanding context and in developing context-aware applications are discussed, which are increasingly important in the fields of handheld and ubiquitous computing, where the user?s context is changing rapidly.
Abstract: When humans talk with humans, they are able to use implicit situational information, or context, to increase the conversational bandwidth. Unfortunately, this ability to convey ideas does not transfer well to humans interacting with computers. In traditional interactive computing, users have an impoverished mechanism for providing input to computers. By improving the computer’s access to context, we increase the richness of communication in human-computer interaction and make it possible to produce more useful computational services. The use of context is increasingly important in the fields of handheld and ubiquitous computing, where the user?s context is changing rapidly. In this panel, we want to discuss some of the research challenges in understanding context and in developing context-aware applications.
4,734 citations
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Alexander A. Aarts, Joanna E. Anderson1, Christopher J. Anderson2, Peter Raymond Attridge3 +287 more•Institutions (116)
TL;DR: A large-scale assessment suggests that experimental reproducibility in psychology leaves a lot to be desired, and correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Abstract: Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
4,564 citations
Authors
Showing all 9627 results
Name | H-index | Papers | Citations |
---|---|---|---|
David Miller | 203 | 2573 | 204840 |
Raymond J. Dolan | 196 | 919 | 138540 |
David J. Brooks | 152 | 1056 | 94335 |
Andrew J. Lees | 140 | 877 | 91605 |
Nick C. Fox | 139 | 748 | 93036 |
David A. Jackson | 136 | 1095 | 68352 |
Alan J. Thompson | 131 | 718 | 82324 |
John S. Duncan | 130 | 898 | 79193 |
Jonathan D. Cohen | 129 | 448 | 113749 |
Peter Brown | 129 | 908 | 68853 |
Martin N. Rossor | 128 | 670 | 95743 |
Doron Aurbach | 126 | 797 | 69313 |
Nicholas W. Wood | 123 | 614 | 66270 |
Leon O. Chua | 122 | 824 | 71612 |
Jun Yu | 121 | 1174 | 81186 |