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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.


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Journal ArticleDOI
TL;DR: This review is intended to give a general background to the use of cyclodextrin as solubilizers as well as highlight kinetic and thermodynamic tools and parameters useful in the study of drug Solubilization bycyclodextrins.

1,674 citations

Journal ArticleDOI
TL;DR: The authors examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects.
Abstract: We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 x 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 x 10(-9)), ANK3 (rs10994359, P = 2.5 x 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 x 10(-9)).

1,671 citations

Journal ArticleDOI
TL;DR: In this article, a global mean distribution for surface water pCO2 over the global oceans in non-El Nino conditions has been constructed with spatial resolution of 4° (latitude) × 5° (longitude) for a reference year 2000 based upon about 3 million measurements of surface water PCO2 obtained from 1970 to 2007.
Abstract: A climatological mean distribution for the surface water pCO2 over the global oceans in non-El Nino conditions has been constructed with spatial resolution of 4° (latitude) ×5° (longitude) for a reference year 2000 based upon about 3 million measurements of surface water pCO2 obtained from 1970 to 2007. The database used for this study is about 3 times larger than the 0.94 million used for our earlier paper [Takahashi et al., 2002. Global sea–air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature effects. Deep-Sea Res. II, 49, 1601–1622]. A time-trend analysis using deseasonalized surface water pCO2 data in portions of the North Atlantic, North and South Pacific and Southern Oceans (which cover about 27% of the global ocean areas) indicates that the surface water pCO2 over these oceanic areas has increased on average at a mean rate of 1.5 μatm y−1 with basin-specific rates varying between 1.2±0.5 and 2.1±0.4 μatm y−1. A global ocean database for a single reference year 2000 is assembled using this mean rate for correcting observations made in different years to the reference year. The observations made during El Nino periods in the equatorial Pacific and those made in coastal zones are excluded from the database. Seasonal changes in the surface water pCO2 and the sea-air pCO2 difference over four climatic zones in the Atlantic, Pacific, Indian and Southern Oceans are presented. Over the Southern Ocean seasonal ice zone, the seasonality is complex. Although it cannot be thoroughly documented due to the limited extent of observations, seasonal changes in pCO2 are approximated by using the data for under-ice waters during austral winter and those for the marginal ice and ice-free zones. The net air–sea CO2 flux is estimated using the sea–air pCO2 difference and the air–sea gas transfer rate that is parameterized as a function of (wind speed)2 with a scaling factor of 0.26. This is estimated by inverting the bomb 14C data using Ocean General Circulation models and the 1979–2005 NCEP-DOE AMIP-II Reanalysis (R-2) wind speed data. The equatorial Pacific (14°N–14°S) is the major source for atmospheric CO2, emitting about +0.48 Pg-C y−1, and the temperate oceans between 14° and 50° in the both hemispheres are the major sink zones with an uptake flux of −0.70 Pg-C y−1 for the northern and −1.05 Pg-C y−1 for the southern zone. The high-latitude North Atlantic, including the Nordic Seas and portion of the Arctic Sea, is the most intense CO2 sink area on the basis of per unit area, with a mean of −2.5 tons-C month−1 km−2. This is due to the combination of the low pCO2 in seawater and high gas exchange rates. In the ice-free zone of the Southern Ocean (50°–62°S), the mean annual flux is small (−0.06 Pg-C y−1) because of a cancellation of the summer uptake CO2 flux with the winter release of CO2 caused by deepwater upwelling. The annual mean for the contemporary net CO2 uptake flux over the global oceans is estimated to be −1.6±0.9 Pg-C y−1, which includes an undersampling correction to the direct estimate of −1.4±0.7 Pg-C y−1. Taking the pre-industrial steady-state ocean source of 0.4±0.2 Pg-C y−1 into account, the total ocean uptake flux including the anthropogenic CO2 is estimated to be −2.0±1.0 Pg-C y−1 in 2000.

1,653 citations

Journal ArticleDOI
TL;DR: In this paper, the Wanninkhof dependence of the CO2 gas transfer velocity has been used to estimate the global ocean CO2 flux in the mean non-El Nino conditions for a reference year 1995.
Abstract: Based on about 940,000 measurements of surface-water pCO2 obtained since the International Geophysical Year of 1956–59, the climatological, monthly distribution of pCO2 in the global surface waters representing mean non-El Nino conditions has been obtained with a spatial resolution of 4°×5° for a reference year 1995. The monthly and annual net sea–air CO2 flux has been computed using the NCEP/NCAR 41-year mean monthly wind speeds. An annual net uptake flux of CO2 by the global oceans has been estimated to be 2.2 (+22% or ?19%) Pg C yr?1 using the (wind speed)2 dependence of the CO2 gas transfer velocity of Wanninkhof (J. Geophys. Res. 97 (1992) 7373). The errors associated with the wind-speed variation have been estimated using one standard deviation (about±2 m s?1) from the mean monthly wind speed observed over each 4°×5° pixel area of the global oceans. The new global uptake flux obtained with the Wanninkhof (wind speed)2 dependence is compared with those obtained previously using a smaller number of measurements, about 250,000 and 550,000, respectively, and are found to be consistent within±0.2 Pg C yr?1. This estimate for the global ocean uptake flux is consistent with the values of 2.0±0.6 Pg C yr?1 estimated on the basis of the observed changes in the atmospheric CO2 and oxygen concentrations during the 1990s (Nature 381 (1996) 218; Science 287 (2000) 2467). However, if the (wind speed)3 dependence of Wanninkhof and McGillis (Res. Lett. 26 (1999) 1889) is used instead, the annual ocean uptake as well as the sensitivity to wind-speed variability is increased by about 70%. A zone between 40° and 60° latitudes in both the northern and southern hemispheres is found to be a major sink for atmospheric CO2. In these areas, poleward-flowing warm waters meet and mix with the cold subpolar waters rich in nutrients. The pCO2 in the surface water is decreased by the cooling effect on warm waters and by the biological drawdown of pCO2 in subpolar waters. High wind speeds over these low pCO2 waters increase the CO2 uptake rate by the ocean waters. The pCO2 in surface waters of the global oceans varies seasonally over a wide range of about 60% above and below the current atmospheric pCO2 level of about 360 ?atm. A global map showing the seasonal amplitude of surface-water pCO2 is presented. The effect of biological utilization of CO2 is differentiated from that of seasonal temperature changes using seasonal temperature data. The seasonal amplitude of surface-water pCO2 in high-latitude waters located poleward of about 40° latitude and in the equatorial zone is dominated by the biology effect, whereas that in the temperate gyre regions is dominated by the temperature effect. These effects are about 6 months out of phase. Accordingly, along the boundaries between these two regimes, they tend to cancel each other, forming a zone of small pCO2 amplitude. In the oligotrophic waters of the northern and southern temperate gyres, the biology effect is about 35 ?atm on average. This is consistent with the biological export flux estimated by Laws et al. (Glob. Biogeochem. Cycles 14 (2000) 1231). Small areas such as the northwestern Arabian Sea and the eastern equatorial Pacific, where seasonal upwelling occurs, exhibit intense seasonal changes in pCO2 due to the biological drawdown of CO2.

1,637 citations

Journal ArticleDOI
TL;DR: The Random Forest classifier uses bagging, or bootstrap aggregating, to form an ensemble of classification and regression tree (CART)-like classifiers, which is computationally much lighter than methods based on boosting and somewhat lighter than simple bagging.

1,634 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