Institution
University of Bergen
Education•Bergen, Hordaland, Norway•
About: University of Bergen is a education organization based out in Bergen, Hordaland, Norway. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 17106 authors who have published 52492 publications receiving 2009844 citations. The organization is also known as: Universitetet i Bergen & Universitas Bergensis.
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TL;DR: The prospects of approximately identifying an unknown taxon, even to the correct genus of subtribe Tanytarsina, are not good if a well-matching cox1 sequence is not already available in the library, because both neighbour joining and maximum parsimony failed to reconstruct monophyletic genera.
296 citations
TL;DR: To avoid over-diagnosing people for high level of fatigue, the threshold for high fatigue probably should be 5 on the FSS scale instead of 4 as had been suggested originally, but further validation of the cut-off point is needed.
Abstract: Objective: A study was undertaken to test the psychometric properties of the Fatigue Severity Scale (FSS), and to explore the relationship between fatigue and sociodemographic variables in the gene...
295 citations
University of Leicester1, Walter and Eliza Hall Institute of Medical Research2, University of Melbourne3, Brigham and Women's Hospital4, GlaxoSmithKline5, Mahidol University6, University of Arizona7, University of Oxford8, University of British Columbia9, University of Cambridge10, Imperial College London11, Greifswald University Hospital12, University of Edinburgh13, University of Liverpool14, Sir Charles Gairdner Hospital15, Swiss Tropical and Public Health Institute16, Science for Life Laboratory17, University of Helsinki18, University of Tampere19, University of Bergen20, Johns Hopkins University21, Laval University22, University Medical Center Groningen23, Icahn School of Medicine at Mount Sinai24, Anschutz Medical Campus25, Peking University26, Uppsala University27, Wellcome Trust Centre for Human Genetics28, Merck & Co.29, University of Aberdeen30, University of Münster31, University of Nottingham32, University of Dundee33, Autonomous University of Barcelona34, VA Boston Healthcare System35, University of California, San Francisco36, Princeton University37, Turku University Hospital38, University of Split39, University of Basel40, University of Western Australia41, Wellcome Trust Sanger Institute42, St George's, University of London43, National Institute for Health Research44
TL;DR: In this paper, a genome-wide association study in 400,102 individuals of European ancestry was conducted to define 279 lung function signals, 139 of which are new and the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups.
Abstract: Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.
295 citations
State University of New York Upstate Medical University1, Heidelberg University2, University of Melbourne3, Capital Medical University4, Harvard University5, Monash University, Clayton campus6, Icahn School of Medicine at Mount Sinai7, Montreal Children's Hospital8, Universidade Federal do Rio Grande do Sul9, Peking University10, University of Southampton11, University of Toronto12, University of Washington13, King Khalid University14, King's College London15, Aga Khan University16, Karolinska Institutet17, Radboud University Nijmegen18, Vrije Universiteit Brussel19, University of Nottingham20, Aarhus University21, University of Cologne22, Trinity College, Dublin23, University of Würzburg24, University of Bergen25, University Medical Center Groningen26, University of Wyoming27, University of California, San Francisco28, University of California, Berkeley29, Nottinghamshire Healthcare NHS Foundation Trust30, Duke University31, University of Amsterdam32, Örebro University33, Chongqing Medical University34, Tel Aviv University35, Washington University in St. Louis36, Federal University of Rio de Janeiro37, University College Cork38, University of British Columbia39, University of Pittsburgh40, Oregon Health & Science University41, University of Montpellier42, University of Ibadan43, University of São Paulo44, Hebrew University of Jerusalem45, University of Sydney46, Jawaharlal Institute of Postgraduate Medical Education and Research47, University of Canterbury48, Autonomous University of Barcelona49, Stellenbosch University50, University of California, Davis51, National Medical College52, Hofstra University53, University of Texas Health Science Center at Houston54, University of Southern Denmark55, University of California, Irvine56, Cardiff University57, Okinawa Institute of Science and Technology58, HU University of Applied Sciences Utrecht59, Katholieke Universiteit Leuven60, University of the Free State61, Johns Hopkins University62, University of Turin63, University of Zurich64
TL;DR: In this article, the authors presented 208 empirically supported statements about ADHD using meta-analysis, which allow for firm statements about the nature, course, outcome causes and treatments for disorders that are useful for reducing misconceptions and stigma.
295 citations
University of Vermont1, Massey University2, National Autonomous University of Mexico3, National Tsing Hua University4, University of Connecticut5, James Cook University6, University of Ottawa7, North Carolina State University8, National Museum of Natural History9, University of Oregon10, University of Bergen11, University of California, San Diego12, University of Colorado Boulder13, University of St Andrews14, University of Copenhagen15, University of Kansas16, Harvard University17
TL;DR: Computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges in an environmentally heterogeneous, gridded domain and three of the 'control knobs' for a general simulation model that specify simple rules for dispersal, evolutionary origins and environmental gradients are described.
Abstract: Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve-fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve-fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the 'control knobs' for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography.
294 citations
Authors
Showing all 17370 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Stephen V. Faraone | 188 | 1427 | 140298 |
| Patrick O. Brown | 183 | 755 | 200985 |
| Anil K. Jain | 183 | 1016 | 192151 |
| Marc Weber | 167 | 2716 | 153502 |
| Johan Auwerx | 158 | 653 | 95779 |
| Leif Groop | 158 | 919 | 136056 |
| Charles M. Perou | 156 | 573 | 202951 |
| Bart Staels | 152 | 824 | 86638 |
| Zhenwei Yang | 150 | 956 | 109344 |
| G. Eigen | 148 | 2188 | 117450 |
| Thomas Lohse | 148 | 1237 | 101631 |
| Marco Costa | 146 | 1458 | 105096 |
| Timothy P. Hughes | 145 | 831 | 91357 |
| Hermann Kolanoski | 145 | 1279 | 96152 |
| Kjell Fuxe | 142 | 1479 | 89846 |