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Institution

University of Iceland

EducationReykjavik, 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
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Journal ArticleDOI
TL;DR: The proposed SVM-based fusion approach outperforms all other approaches and significantly improves the results of a single SVM, which is trained on the whole multisensor data set.
Abstract: The classification of multisensor data sets, consisting of multitemporal synthetic aperture radar data and optical imagery, is addressed. The concept is based on the decision fusion of different outputs. Each data source is treated separately and classified by a support vector machine (SVM). Instead of fusing the final classification outputs (i.e., land cover classes), the original outputs of each SVM discriminant function are used in the subsequent fusion process. This fusion is performed by another SVM, which is trained on the a priori outputs. In addition, two voting schemes are applied to create the final classification results. The results are compared with well-known parametric and nonparametric classifier methods, i.e., decision trees, the maximum-likelihood classifier, and classifier ensembles. The proposed SVM-based fusion approach outperforms all other approaches and significantly improves the results of a single SVM, which is trained on the whole multisensor data set.

397 citations

Journal ArticleDOI
A. A. Abdo1, Markus Ackermann2, Marco Ajello2, Alice Allafort2  +173 moreInstitutions (34)
11 Feb 2011-Science
TL;DR: Two separate gamma-ray flares from a young and energetic pulsar powers the well-known Crab Nebula are described and it is suggested that the gamma rays were emitted via synchrotron radiation from peta–electron-volt electrons in a region smaller than 1.4 × 10−2 parsecs.
Abstract: A young and energetic pulsar powers the well-known Crab Nebula. Here, we describe two separate gamma-ray (photon energy greater than 100 mega-electron volts) flares from this source detected by the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. The first flare occurred in February 2009 and lasted approximately 16 days. The second flare was detected in September 2010 and lasted approximately 4 days. During these outbursts, the gamma-ray flux from the nebula increased by factors of four and six, respectively. The brevity of the flares implies that the gamma rays were emitted via synchrotron radiation from peta-electron-volt (10(15) electron volts) electrons in a region smaller than 1.4 × 10(-2) parsecs. These are the highest-energy particles that can be associated with a discrete astronomical source, and they pose challenges to particle acceleration theory.

395 citations

Journal ArticleDOI
María Soler Artigas1, Daan W. Loth2, Louise V. Wain1, Sina A. Gharib3  +189 moreInstitutions (64)
TL;DR: This article identified new regions showing association with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2.
Abstract: Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.

394 citations

Journal ArticleDOI
TL;DR: In this article, a stochastic volatility model is used to estimate daily asset price dynamics, and the model is estimated by integrating latent volatility out of the joint density of prices and volatility to obtain the marginal density.

394 citations

Journal ArticleDOI
Jason Flannick1, Jason Flannick2, Gudmar Thorleifsson3, Nicola L. Beer4, Nicola L. Beer2, Suzanne B.R. Jacobs2, Niels Grarup5, Noël P. Burtt2, Anubha Mahajan4, Christian Fuchsberger6, Gil Atzmon7, Rafn Benediktsson, John Blangero8, Donald W. Bowden9, Ivan Brandslund10, Julia Brosnan11, Frank Burslem, John C. Chambers12, John C. Chambers13, John C. Chambers14, Yoon Shin Cho15, Cramer Christensen10, Desiree Douglas16, Ravindranath Duggirala8, Zachary Dymek2, Yossi Farjoun2, Timothy Fennell2, Pierre Fontanillas2, Tom Forsén17, Stacey Gabriel2, Benjamin Glaser, Daniel F. Gudbjartsson3, Craig L. Hanis18, Torben Hansen5, Torben Hansen10, Astradur B. Hreidarsson, Kristian Hveem19, Erik Ingelsson20, Erik Ingelsson4, Bo Isomaa, Stefan Johansson21, Torben Jørgensen22, Torben Jørgensen5, Marit E. Jørgensen23, Sekar Kathiresan2, Sekar Kathiresan1, Augustine Kong3, Jaspal S. Kooner13, Jaspal S. Kooner12, Jaspal S. Kooner14, Jasmina Kravic16, Markku Laakso24, Jong-Young Lee, Lars Lind20, Cecilia M. Lindgren4, Cecilia M. Lindgren2, Allan Linneberg5, Gisli Masson3, Thomas Meitinger25, Karen L. Mohlke26, Anders Molven21, Andrew P. Morris4, Andrew P. Morris27, Shobha Potluri11, Rainer Rauramaa24, Rasmus Ribel-Madsen5, Ann Marie Richard11, Tim Rolph11, Veikko Salomaa28, Ayellet V. Segrè2, Ayellet V. Segrè1, Hanna Skärstrand16, Valgerdur Steinthorsdottir3, Heather M. Stringham6, Patrick Sulem3, E. Shyong Tai29, Yik Ying Teo30, Yik Ying Teo29, Tanya M. Teslovich6, Unnur Thorsteinsdottir31, Unnur Thorsteinsdottir3, Jeff K. Trimmer11, Tiinamaija Tuomi17, Jaakko Tuomilehto32, Jaakko Tuomilehto33, Jaakko Tuomilehto28, Fariba Vaziri-Sani16, Benjamin F. Voight34, Benjamin F. Voight2, James G. Wilson35, Michael Boehnke6, Mark I. McCarthy36, Mark I. McCarthy4, Pål R. Njølstad2, Pål R. Njølstad21, Oluf Pedersen5, Leif Groop17, Leif Groop16, David R. Cox11, Kari Stefansson3, Kari Stefansson31, David Altshuler1, David Altshuler37, David Altshuler2 
TL;DR: In this article, the authors identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels.
Abstract: Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ~150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10(-6)), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (-0.17 s.d., P = 4.6 × 10(-4)). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.

394 citations


Authors

Showing all 5561 results

NameH-indexPapersCitations
Albert Hofman2672530321405
Kari Stefansson206794174819
Ronald Klein1941305149140
Eric Boerwinkle1831321170971
Unnur Thorsteinsdottir167444121009
Vilmundur Gudnason159837123802
Hakon Hakonarson152968101604
Bernhard O. Palsson14783185051
Andrew T. Hattersley146768106949
Fernando Rivadeneira14662886582
Rattan Lal140138387691
Jonathan G. Seidman13756389782
Christine E. Seidman13451967895
Augustine Kong13423789818
Timothy M. Frayling133500100344
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202377
2022209
20211,222
20201,118
20191,140
20181,070