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Bristol, United Kingdom

The University of Bristol is a red brick research university located in Bristol, United Kingdom. It received its Royal Charter in 1909, and its predecessor institution, University College, Bristol, had been in existence since 1876.Bristol has been ranked 29th by the QS World University Rankings, and is ranked amongst the top ten of UK universities by QS, THE, and ARWU. A highly selective institution, it has an average of 14 applicants for each undergraduate place.Bristol is organised into six academic faculties composed of multiple schools and departments running over 200 undergraduate courses situated in the Clifton area along with three of its nine halls of residence. The other six halls are located in Stoke Bishop, an outer city suburb located 1.8 miles away. The University had a total income of £459.2 million in 2012/13, of which £120.1 million was from research grants and contracts. It is the largest independent employer in Bristol.Current academics include 21 Fellows of the Academy of Medical science, 13 Fellows of the British Academy, 13 Fellows of the Royal Academy of Engineering and 40 Fellows of the Royal Society.Bristol is a member of the Russell Group of research-intensive British universities, the European-wide Coimbra Group and the Worldwide Universities Network, of which the University's Vice-Chancellor Eric Thomas was chairman from 2005 to 2007. In addition, the University holds an Erasmus Charter, sending more than 500 students per year to partner institutions in Europe. Wikipedia.

Adams J.C.,University of Bristol
Cold Spring Harbor perspectives in biology | Year: 2011

Thrombospondins are evolutionarily conserved, calcium-binding glycoproteins that undergo transient or longer-term interactions with other extracellular matrix components. They share properties with other matrix molecules, cytokines, adaptor proteins, and chaperones, modulate the organization of collagen fibrils, and bind and localize an array of growth factors or proteases. At cell surfaces, interactions with an array of receptors activate cell-dependent signaling and phenotypic outcomes. Through these dynamic, pleiotropic, and context-dependent pathways, mammalian thrombospondins contribute to wound healing and angiogenesis, vessel wall biology, connective tissue organization, and synaptogenesis. We overview the domain organization and structure of thrombospondins, key features of their evolution, and their cell biology. We discuss their roles in vivo, associations with human disease, and ongoing translational applications. In many respects, we are only beginning to appreciate the important roles of these proteins in physiology and pathology. Source

Harvey J.N.,University of Bristol
Wiley Interdisciplinary Reviews: Computational Molecular Science | Year: 2014

Many chemical reactions involve one or more changes in the total electronic spin of the reacting system as part of one or more elementary steps. Computational and theoretical methods that can be used to understand such reaction steps are described, and a number of recent examples are highlighted. A particularly strong focus is given to general rules that govern multistep reactions of this type. The two most important rules are (1) that spin-state change without change in atom connectivity, or spin crossover, is facile and rapid, at least when it is exothermic; and (2) that reactions involving spin-state change and changes in atom connectivity tend to prefer stepwise mechanisms in which spin crossover steps alternate with spin-allowed bond-making and breaking steps. © 2013 John Wiley & Sons, Ltd. Source

Howard-Jones P.A.,University of Bristol
Nature Reviews Neuroscience | Year: 2014

For several decades, myths about the brain-neuromyths-have persisted in schools and colleges, often being used to justify ineffective approaches to teaching. Many of these myths are biased distortions of scientific fact. Cultural conditions, such as differences in terminology and language, have contributed to a 'gap' between neuroscience and education that has shielded these distortions from scrutiny. In recent years, scientific communications across this gap have increased, although the messages are often distorted by the same conditions and biases as those responsible for neuromyths. In the future, the establishment of a new field of inquiry that is dedicated to bridging neuroscience and education may help to inform and to improve these communications. © 2015 Macmillan Publishers Limited. Source

We set out a generalized linear model framework for the synthesis of data from randomized controlled trials. A common model is described, taking the form of a linear regression for both fixed and random effects synthesis, which can be implemented with normal, binomial, Poisson, and multinomial data. The familiar logistic model for meta-analysis with binomial data is a generalized linear model with a logit link function, which is appropriate for probability outcomes. The same linear regression framework can be applied to continuous outcomes, rate models, competing risks, or ordered category outcomes by using other link functions, such as identity, log, complementary log-log, and probit link functions. The common core model for the linear predictor can be applied to pairwise meta-analysis, indirect comparisons, synthesis of multiarm trials, and mixed treatment comparisons, also known as network meta-analysis, without distinction. We take a Bayesian approach to estimation and provide WinBUGS program code for a Bayesian analysis using Markov chain Monte Carlo simulation. An advantage of this approach is that it is straightforward to extend to shared parameter models where different randomized controlled trials report outcomes in different formats but from a common underlying model. Use of the generalized linear model framework allows us to present a unified account of how models can be compared using the deviance information criterion and how goodness of fit can be assessed using the residual deviance. The approach is illustrated through a range of worked examples for commonly encountered evidence formats. Source

Beaumont M.A.,University of Bristol
Annual Review of Ecology, Evolution, and Systematics | Year: 2010

In the past 10years a statistical technique, approximate Bayesian computation (ABC), has been developed that can be used to infer parameters and choose between models in the complicated scenarios that are often considered in the environmental sciences. For example, based on gene sequence and microsatellite data, the method has been used to choose between competing models of human demographic history as well as to infer growth rates, times of divergence, and other parameters. The method fits naturally in the Bayesian inferential framework, and a brief overview is given of the key concepts. Three main approaches to ABC have been developed, and these are described and compared. Although the method arose in population genetics, ABC is increasingly used in other fields, including epidemiology, systems biology, ecology, and agent-based modeling, and many of these applications are briefly described. Copyright © 2010 by Annual Reviews. All rights reserved. Source

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