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
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deCODE genetics1, University of Iceland2, University of Tampere3, Vanderbilt University4, University of Zaragoza5, Radboud University Nijmegen Medical Centre6, Radboud University Nijmegen7, Washington University in St. Louis8, Northwestern University9, University of Turin10, Veterans Health Administration11
TL;DR: In a multivariate analysis using 22 prostate cancer risk variants typed in the Icelandic population, it is estimated that carriers in the top 1.3% of the risk distribution are at a 2.5 times greater risk of developing the disease than members of the general population.
Abstract: We report a prostate cancer genome-wide association follow-on study. We discovered four variants associated with susceptibility to prostate cancer in several European populations: rs10934853[A] (OR = 1.12, P = 2.9 x 10(-10)) on 3q21.3; two moderately correlated (r2 = 0.07) variants, rs16902094[G] (OR = 1.21, P = 6.2 x 10(-15)) and rs445114[T] (OR = 1.14, P = 4.7 x 10(-10)), on 8q24.21; and rs8102476[C] (OR = 1.12, P = 1.6 x 10(-11)) on 19q13.2. We also refined a previous association signal on 11q13 with the SNP rs11228565[A] (OR = 1.23, P = 6.7 x 10(-12)). In a multivariate analysis using 22 prostate cancer risk variants typed in the Icelandic population, we estimated that carriers in the top 1.3% of the risk distribution are at a 2.5 times greater risk of developing the disease than members of the general population.
362 citations
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National Institutes of Health1, Boston University2, University of Washington3, Johns Hopkins University4, Technische Universität München5, Erasmus University Rotterdam6, University of Mainz7, University of Texas Health Science Center at Houston8, Ludwig Maximilian University of Munich9, Harvard University10, University of Iceland11, Wake Forest University12, Group Health Cooperative13, University of Minnesota14, Cedars-Sinai Medical Center15, University of North Carolina at Chapel Hill16, United States Department of Veterans Affairs17
TL;DR: Meta-analyses of genome-wide association studies for atrial fibrillation in participants from five community-based cohorts identified a new locus for AF as ZFHX3, rs2106261, which was replicated in an independent cohort from the German AF Network.
Abstract: We conducted meta-analyses of genome-wide association studies for atrial fibrillation (AF) in participants from five community-based cohorts. Meta-analyses of 896 prevalent (15,768 referents) and 2,517 incident (21,337 referents) AF cases identified a new locus for AF (ZFHX3, rs2106261, risk ratio RR = 1.19; P = 2.3 x 10(-7)). We replicated this association in an independent cohort from the German AF Network (odds ratio = 1.44; P = 1.6 x 10(-11); combined RR = 1.25; combined P = 1.8 x 10(-15)).
360 citations
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13 Sep 2016TL;DR: This paper analyzes the challenges and opportunities that big data bring in the context of remote sensing applications and describes the most challenging issues in managing, processing, and efficient exploitation of big data for remote sensing problems.
Abstract: Every day a large number of Earth observation (EO) spaceborne and airborne sensors from many different countries provide a massive amount of remotely sensed data. Those data are used for different applications, such as natural hazard monitoring, global climate change, urban planning, etc. The applications are data driven and mostly interdisciplinary. Based on this it can truly be stated that we are now living in the age of big remote sensing data. Furthermore, these data are becoming an economic asset and a new important resource in many applications. In this paper, we specifically analyze the challenges and opportunities that big data bring in the context of remote sensing applications. Our focus is to analyze what exactly does big data mean in remote sensing applications and how can big data provide added value in this context. Furthermore, this paper describes the most challenging issues in managing, processing, and efficient exploitation of big data for remote sensing problems. In order to illustrate the aforementioned aspects, two case studies discussing the use of big data in remote sensing are demonstrated. In the first test case, big data are used to automatically detect marine oil spills using a large archive of remote sensing data. In the second test case, content-based information retrieval is performed using high-performance computing (HPC) to extract information from a large database of remote sensing images, collected after the terrorist attack to the World Trade Center in New York City. Both cases are used to illustrate the significant challenges and opportunities brought by the use of big data in remote sensing applications.
359 citations
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University of Oxford1, St George's, University of London2, Ludwig Maximilian University of Munich3, University of Edinburgh4, University of Aberdeen5, Jagiellonian University6, Lund University7, Katholieke Universiteit Leuven8, Flanders Institute for Biotechnology9, Imperial College London10, Broad Institute11, University of Maryland, Baltimore12, University of Cincinnati13, National Institutes of Health14, Max Planck Society15, University of Münster16, Harvard University17, Wellcome Trust Sanger Institute18, deCODE genetics19, University of Iceland20, University of Newcastle21, University of Cambridge22, University of Western Australia23, King's College London24, University of Queensland25, University College London26, University of London27, Trinity College, Dublin28, Wellcome Trust29, Queen Mary University of London30, Ninewells Hospital31, National Institute for Health Research32, University of Virginia33, Veterans Health Administration34, Mayo Clinic35, University of Glasgow36
TL;DR: A new association for large vessel stroke within HDAC9 (encoding histone deacetylase 9) on chromosome 7p21.1 is identified, which suggests distinct genetic architectures for different stroke subtypes.
Abstract: Genetic factors have been implicated in stroke risk, but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) for ischemic stroke and its subtypes in 3,548 affected individuals and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 affected individuals and 6,281 controls. We replicated previous associations for cardioembolic stroke near PITX2 and ZFHX3 and for large vessel stroke at a 9p21 locus. We identified a new association for large vessel stroke within HDAC9 (encoding histone deacetylase 9) on chromosome 7p21.1 (including further replication in an additional 735 affected individuals and 28,583 controls) (rs11984041; combined P = 1.87 × 10(-11); odds ratio (OR) = 1.42, 95% confidence interval (CI) = 1.28-1.57). All four loci exhibited evidence for heterogeneity of effect across the stroke subtypes, with some and possibly all affecting risk for only one subtype. This suggests distinct genetic architectures for different stroke subtypes.
358 citations
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TL;DR: In this paper, the gamma-ray activity of the high-synchrotron-peaked BL Lacertae object Markarian 421 (Mrk 421) during the first 1.5 years of Fermi operation was reported.
Abstract: We report on the gamma-ray activity of the high-synchrotron-peaked BL Lacertae object Markarian 421 (Mrk 421) during the first 1.5 years of Fermi operation, from 2008 August 5 to 2010 March 12. We find that the Large Area Telescope (LAT) gamma-ray spectrum above 0.3 GeV can be well described by a power-law function with photon index Gamma = 1.78 +/- 0.02 and average photon flux F(>0.3 GeV) = (7.23 +/- 0.16) x 10(-8) ph cm(-2) s(-1). Over this time period, the Fermi-LAT spectrum above 0.3 GeV was evaluated on seven-day-long time intervals, showing significant variations in the photon flux (up to a factor similar to 3 from the minimum to the maximum flux) but mild spectral variations. The variability amplitude at X-ray frequencies measured by RXTE/ASM and Swift/BAT is substantially larger than that in gamma-rays measured by Fermi-LAT, and these two energy ranges are not significantly correlated. We also present the first results from the 4.5 month long multifrequency campaign on Mrk 421, which included the VLBA, Swift, RXTE, MAGIC, the F-GAMMA, GASP-WEBT, and other collaborations and instruments that provided excellent temporal and energy coverage of the source throughout the entire campaign (2009 January 19 to 2009 June 1). During this campaign, Mrk 421 showed a low activity at all wavebands. The extensive multi-instrument (radio to TeV) data set provides an unprecedented, complete look at the quiescent spectral energy distribution (SED) for this source. The broadband SED was reproduced with a leptonic (one-zone synchrotron self-Compton) and a hadronic model (synchrotron proton blazar). Both frameworks are able to describe the average SED reasonably well, implying comparable jet powers but very different characteristics for the blazar emission site.
357 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 |