Institution
University of Iceland
Education•Reykjavik, Suðurnes, Iceland•
About: University of Iceland is a education organization based out in Reykjavik, Suðurnes, Iceland. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 5423 authors who have published 16199 publications receiving 694762 citations. The organization is also known as: Háskóli Íslands.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: The nature of secondary equilibria and competition between cyclodextrins and rheologically important biopolymers such as mucin are assessed to give a complete picture of the effect of these starch derivatives.
266 citations
••
TL;DR: The proposed PCA-EPFs method for HSI classification sharply improves the accuracy of the SVM classifier with respect to the standard edge-preserving filtering-based feature extraction method, and other widely used spectral-spatial classifiers.
Abstract: Edge-preserving features (EPFs) obtained by the application of edge-preserving filters to hyperspectral images (HSIs) have been found very effective in characterizing significant spectral and spatial structures of objects in a scene. However, a direct use of the EPFs can be insufficient to provide a complete characterization of spatial information when objects of different scales are present in the considered images. Furthermore, the edge-preserving smoothing operation unavoidably decreases the spectral differences among objects of different classes, which may affect the following classification. To overcome these problems, in this paper, a novel principal component analysis (PCA)-based EPFs (PCA-EPFs) method for HSI classification is proposed, which consists of the following steps. First, the standard EPFs are constructed by applying edge-preserving filters with different parameter settings to the considered image, and the resulting EPFs are stacked together. Next, the spectral dimension of the stacked EPFs is reduced with the PCA, which not only can represent the EPFs in the mean square sense but also highlight the separability of pixels in the EPFs. Finally, the resulting PCA-EPFs are classified by a support vector machine (SVM) classifier. Experiments performed on several real hyperspectral data sets show the effectiveness of the proposed PCA-EPFs, which sharply improves the accuracy of the SVM classifier with respect to the standard edge-preserving filtering-based feature extraction method, and other widely used spectral-spatial classifiers.
265 citations
••
TL;DR: Curcumin is more active than the derivatives investigated and that the free phenolic hydroxyl group may be essential for the scavenging properties, and the two halves of the symmetric curcumin molecule act as two separate units and scavenge one radical each.
265 citations
••
University of London1, Imperial College London2, Mahidol University3, Imperial College Healthcare4, University of California, San Francisco5, Virginia Commonwealth University6, Erasmus University Rotterdam7, Uppsala University8, University of Groningen9, French Institute of Health and Medical Research10, University of Paris-Sud11, Utrecht University12, Centre national de la recherche scientifique13, University of Mainz14, Indiana University15, University of Tartu16, University of Salamanca17, University of California, Los Angeles18, Pierre-and-Marie-Curie University19, University of Iceland20, University of Oulu21, University of Washington22, University of Connecticut23, VU University Amsterdam24, University of Helsinki25, University of Cambridge26, King's College London27, University of Turin28, University of Oxford29, University of Erlangen-Nuremberg30, QIMR Berghofer Medical Research Institute31, Semmelweis University32, Leiden University33, Wellcome Trust Sanger Institute34, GlaxoSmithKline35, Leipzig University36, University of Lausanne37, Ludwig Maximilian University of Munich38
TL;DR: A genome-wide association study meta-analysis of ∼2.5 million directly genotyped or imputed SNPs with alcohol consumption among 12 population-based samples of European ancestry finds a genotype-specific expression of AUTS2 in 96 human prefrontal cortex samples and finds a regulator of alcohol consumption.
Abstract: Alcohol consumption is a moderately heritable trait, but the genetic basis in humans is largely unknown, despite its clinical and societal importance. We report a genome-wide association study meta-analysis of similar to 2.5 million directly genotyped or imputed SNPs with alcohol consumption (gram per day per kilogram body weight) among 12 population-based samples of European ancestry, comprising 26,316 individuals, with replication genotyping in an additional 21,185 individuals. SNP rs6943555 in autism susceptibility candidate 2 gene (AUTS2) was associated with alcohol consumption at genome-wide significance (P = 4 x 10(-8) to P = 4 x 10(-9)). We found a genotype-specific expression of AUTS2 in 96 human prefrontal cortex samples (P = 0.026) and significant (P < 0.017) differences in expression of AUTS2 in whole-brain extracts of mice selected for differences in voluntary alcohol consumption. Downregulation of an AUTS2 homolog caused reduced alcohol sensitivity in Drosophila (P < 0.001). Our finding of a regulator of alcohol consumption adds knowledge to our understanding of genetic mechanisms influencing alcohol drinking behavior.
265 citations
••
King's College London1, University of Exeter2, University of Oxford3, Massachusetts Institute of Technology4, Centre national de la recherche scientifique5, Erasmus University Rotterdam6, Boston University7, National Institutes of Health8, University of Michigan9, University of Edinburgh10, Johns Hopkins University11, Harvard University12, deCODE genetics13, Medical Research Council14, Lund University15, Cedars-Sinai Medical Center16, University of Texas Health Science Center at Houston17, University of Düsseldorf18, University of Freiburg19, University of North Carolina at Chapel Hill20, University of Minnesota21, University of Lübeck22, McGill University23, University of Iceland24, Hannover Medical School25, University of Dundee26, Imperial College London27
TL;DR: Evidence is provided that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2abetes.
Abstract: Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI = 30 Kg/m(2)). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI = 30 kg/m(2)), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4610 29, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A-previously identified in South Asians but not Europeans-was associated with type 2 diabetes in obese cases (P = 1.3 x 10(-8), OR= 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2 x 10(-14). This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2 x 10(-16). This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
265 citations
Authors
Showing all 5561 results
Name | H-index | Papers | Citations |
---|---|---|---|
Albert Hofman | 267 | 2530 | 321405 |
Kari Stefansson | 206 | 794 | 174819 |
Ronald Klein | 194 | 1305 | 149140 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Unnur Thorsteinsdottir | 167 | 444 | 121009 |
Vilmundur Gudnason | 159 | 837 | 123802 |
Hakon Hakonarson | 152 | 968 | 101604 |
Bernhard O. Palsson | 147 | 831 | 85051 |
Andrew T. Hattersley | 146 | 768 | 106949 |
Fernando Rivadeneira | 146 | 628 | 86582 |
Rattan Lal | 140 | 1383 | 87691 |
Jonathan G. Seidman | 137 | 563 | 89782 |
Christine E. Seidman | 134 | 519 | 67895 |
Augustine Kong | 134 | 237 | 89818 |
Timothy M. Frayling | 133 | 500 | 100344 |