scispace - formally typeset
Search or ask a question
Institution

Glostrup Hospital

HealthcareGlostrup Municipality, Denmark
About: Glostrup Hospital is a healthcare organization based out in Glostrup Municipality, Denmark. It is known for research contribution in the topics: Population & Migraine. The organization has 1844 authors who have published 2237 publications receiving 105232 citations.


Papers
More filters
Journal ArticleDOI
29 Aug 2013-Nature
TL;DR: The authors' classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.
Abstract: We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.

3,448 citations

Journal ArticleDOI
TL;DR: An artificial neural network method is presented that predicts phosphorylation sites in independent sequences with a sensitivity in the range from 69 % to 96 % and predicts novel phosphorylated sites in the p300/CBP protein that may regulate interaction with transcription factors and histone acetyltransferase activity.

2,984 citations

Journal ArticleDOI
Eleftheria Zeggini1, Laura J. Scott2, Richa Saxena, Benjamin F. Voight, Jonathan Marchini3, T Hu2, de Bakker Piw.4, de Bakker Piw.5, de Bakker Piw.6, Gonçalo R. Abecasis2, Peter Almgren7, Gregers S. Andersen8, Kristin Ardlie4, Kristina Bengtsson Boström, Richard N. Bergman9, Lori L. Bonnycastle10, Knut Borch-Johnsen11, Knut Borch-Johnsen8, Noël P. Burtt4, H Chen12, Peter S. Chines10, Mark J. Daly, P Deodhar10, Ding C-J.2, Doney Asf.13, William L. Duren2, Katherine S. Elliott1, Mike Erdos10, Timothy M. Frayling14, Rachel M. Freathy14, Lauren Gianniny4, Harald Grallert, Niels Grarup8, Christopher J. Groves3, Candace Guiducci4, Torben Hansen8, Christian Herder15, Graham A. Hitman16, Thomas Edward Hughes12, Bo Isomaa, Anne U. Jackson2, Torben Jørgensen17, Augustine Kong18, Kari Kubalanza10, Finny G Kuruvilla6, Finny G Kuruvilla4, Johanna Kuusisto19, Claudia Langenberg20, Hana Lango14, Torsten Lauritzen21, Yun Li2, Cecilia M. Lindgren3, Cecilia M. Lindgren1, Valeriya Lyssenko7, Amanda F. Marvelle22, Christine Meisinger, Kristian Midthjell23, Karen L. Mohlke22, Mario A. Morken10, Andrew D. Morris13, Narisu Narisu10, Peter M. Nilsson7, Katharine R. Owen3, Palmer Cna.13, Felicity Payne24, Perry Jrb.14, E Pettersen23, Carl Platou23, Inga Prokopenko3, Inga Prokopenko1, Lu Qi6, Lu Qi5, L Qin22, Nigel W. Rayner3, Nigel W. Rayner1, Matthew G. Rees10, J J Roix12, A Sandbaek11, Beverley M. Shields, Marketa Sjögren7, Valgerdur Steinthorsdottir18, Heather M. Stringham2, Amy J. Swift10, Gudmar Thorleifsson18, Unnur Thorsteinsdottir18, Nicholas J. Timpson1, Nicholas J. Timpson25, Tiinamaija Tuomi26, Jaakko Tuomilehto26, Mark Walker27, Richard M. Watanabe9, Michael N. Weedon14, Cristen J. Willer2, Thomas Illig, Kristian Hveem23, Frank B. Hu5, Frank B. Hu6, Markku Laakso19, Kari Stefansson18, Oluf Pedersen8, Oluf Pedersen11, Nicholas J. Wareham20, Inês Barroso24, Andrew T. Hattersley14, Francis S. Collins10, Leif Groop26, Leif Groop7, Mark I. McCarthy1, Mark I. McCarthy3, Michael Boehnke2, David Altshuler 
TL;DR: The results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D, and detect at least six previously unknown loci with robust evidence for association.
Abstract: Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

1,872 citations

Journal ArticleDOI
TL;DR: A new method for kinase‐specific prediction of phosphorylation sites, NetPhosK, is presented, which extends the earlier and more general tool, netPhos, and the issues of underestimation, over‐prediction and strategies for improving prediction specificity are discussed.
Abstract: Post-translational modifications (PTMs) occur on almost all proteins analyzed to date. The function of a modified protein is often strongly affected by these modifications and therefore increased knowledge about the potential PTMs of a target protein may increase our understanding of the molecular processes in which it takes part. High-throughput methods for the identification of PTMs are being developed, in particular within the fields of proteomics and mass spectrometry. However, these methods are still in their early stages, and it is indeed advantageous to cut down on the number of experimental steps by integrating computational approaches into the validation procedures. Many advanced methods for the prediction of PTMs exist and many are made publicly available. We describe our experiences with the development of prediction methods for phosphorylation and glycosylation sites and the development of PTM-specific databases. In addition, we discuss novel ideas for PTM visualization (exemplified by kinase landscapes) and improvements for prediction specificity (by using ESS--evolutionary stable sites). As an example, we present a new method for kinase-specific prediction of phosphorylation sites, NetPhosK, which extends our earlier and more general tool, NetPhos. The new server, NetPhosK, is made publicly available at the URL http://www.cbs.dtu.dk/services/NetPhosK/. The issues of underestimation, over-prediction and strategies for improving prediction specificity are also discussed.

1,838 citations


Authors

Showing all 1849 results

NameH-indexPapersCitations
Leif Groop158919136056
Torben Jørgensen13588386822
Jes Olesen12480879687
Peter J. Goadsby12394673783
Lars Køber114115577298
Olle Melander10978375911
Louis M. Kunkel10435244428
Lars Edvinsson97100343544
Baha M. Sibai9347030922
Knut Borch-Johnsen8833340123
Mikkel Østergaard8758327162
Sten Madsbad8753228980
Allan Linneberg8557745508
Olaf B. Paulson8545522268
Alan H. Beggs8333626523
Network Information
Related Institutions (5)
Karolinska University Hospital
33.5K papers, 1.2M citations

91% related

Karolinska Institutet
121.1K papers, 6M citations

89% related

Umeå University
53.5K papers, 2.2M citations

84% related

University of Copenhagen
149.7K papers, 5.9M citations

84% related

University of Gothenburg
65.2K papers, 2.6M citations

84% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20226
202163
202065
201940
201843