Institution
University of Copenhagen
Education•Copenhagen, Denmark•
About: University of Copenhagen is a education organization based out in Copenhagen, Denmark. It is known for research contribution in the topics: Population & Medicine. The organization has 57645 authors who have published 149740 publications receiving 5903093 citations. The organization is also known as: Copenhagen University & Københavns Universitet.
Topics: Population, Medicine, Galaxy, Diabetes mellitus, Cancer
Papers published on a yearly basis
Papers
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Lund University1, Stanford University2, Australian National University3, University of Copenhagen4, Karlsruhe Institute of Technology5, Max Planck Society6, Commonwealth Scientific and Industrial Research Organisation7, University of Exeter8, University of Illinois at Urbana–Champaign9, Montana State University10, Oeschger Centre for Climate Change Research11, Imperial College London12, Met Office13, University of Maryland, College Park14
TL;DR: Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, it is shown that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions.
Abstract: The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.
948 citations
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TL;DR: A Bayesian predictor is developed that identifies novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease.
Abstract: We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.
944 citations
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TL;DR: Exercise training is the most potent stimulus to increase skeletal muscle GLUT4 expression, an effect that may partly contribute to improved insulin action and glucose disposal and enhanced muscle glycogen storage following exercise training in health and disease.
Abstract: Glucose is an important fuel for contracting muscle, and normal glucose metabolism is vital for health. Glucose enters the muscle cell via facilitated diffusion through the GLUT4 glucose transporte...
944 citations
01 Jan 2011
TL;DR: Arnaut et al. as mentioned in this paper discuss super-diversity in the context of a translingual ontology and discuss the role of sociolinguistic shibboleths at the institutional gate.
Abstract: CONTENTS 1. Introduction Karel Arnaut , Jan Blommaert, Ben Rampton, and Massimiliano Spotti Part 1: Sketching the paradigm 2. Language and superdiversity Jan Blommaert and Ben Rampton 3. Super-diversity: Elements of an emerging perspective Karel Arnaut 4. From multilingual classification to translingual ontology: A turning point David Parkin Part II: Sociolinguistic complexity 5. Drilling down to the grain in superdiversity Ben Rampton 6. Buffalaxing the other: Superdiversity in action on YouTube Sirpa Leppanen and Ari Hakkinen 7. Polylanguaging in super-diversity Jens Normann Jorgensen, Martha Sif Karrebaek, Lian Malai Madsen, and Janus Spindler Moller 8. 'A typical gentleman': Metapragmatic stereotypes as systems of distinction Adrian Blackledge and Angela Creese 9. Mobility, voice, and symbolic restratification: An ethnography of 'elite migrants' in urban China Jie Dong Part III: Policing complexity 10. Ethnographic linguistic landscape analysis and social change: A case study Jan Blommaert and Ico Maly 11. Superdiversity on the Internet: A case from China Piia Varis and Xuan Wang 12. Translating global experience into institutional models of competency: Linguistic inequalities in the job interview Celia Roberts 13. Sociolinguistic shibboleths at the institutional gate: Language, origin and the construction of asylum seekers' identities Massimiliano Spotti
943 citations
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TL;DR: An eddy covariance system is described in this paper, which uses commercially available instrumentation: a three-axis sonic anemometer and an IR gas analyser which is used in a closed-path mode.
942 citations
Authors
Showing all 58387 results
Name | H-index | Papers | Citations |
---|---|---|---|
Michael Karin | 236 | 704 | 226485 |
Matthias Mann | 221 | 887 | 230213 |
Peer Bork | 206 | 697 | 245427 |
Ronald Klein | 194 | 1305 | 149140 |
Kenneth S. Kendler | 177 | 1327 | 142251 |
Dorret I. Boomsma | 176 | 1507 | 136353 |
Ramachandran S. Vasan | 172 | 1100 | 138108 |
Unnur Thorsteinsdottir | 167 | 444 | 121009 |
Mika Kivimäki | 166 | 1515 | 141468 |
Jun Wang | 166 | 1093 | 141621 |
Anders Björklund | 165 | 769 | 84268 |
Gerald I. Shulman | 164 | 579 | 109520 |
Jaakko Kaprio | 163 | 1532 | 126320 |
Veikko Salomaa | 162 | 843 | 135046 |
Daniel J. Jacob | 162 | 656 | 76530 |