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Träfflista för sökning "WFRF:(Barnes D. R.) srt2:(2020-2024)"

Search: WFRF:(Barnes D. R.) > (2020-2024)

  • Result 1-10 of 71
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1.
  • 2021
  • swepub:Mat__t
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2.
  • Niemi, MEK, et al. (author)
  • 2021
  • swepub:Mat__t
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3.
  • Kanai, M, et al. (author)
  • 2023
  • swepub:Mat__t
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7.
  • Marconi, A., et al. (author)
  • ANDES, the high resolution spectrograph for the ELT : science case, baseline design and path to construction
  • 2022
  • In: GROUND-BASED AND AIRBORNE INSTRUMENTATION FOR ASTRONOMY IX. - : SPIE - International Society for Optical Engineering. - 9781510653504 - 9781510653498
  • Conference paper (peer-reviewed)abstract
    • The first generation of ELT instruments includes an optical-infrared high resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs (UBV, RIZ, YJH) providing a spectral resolution of similar to 100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 mu m with the goal of extending it to 0.35-2.4 mu m with the addition of a K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre-feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Its modularity will ensure that ANDES can be placed entirely on the ELT Nasmyth platform, if enough mass and volume is available, or partly in the Coude room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of more than 200 scientists and engineers which represent the majority of the scientific and technical expertise in the field among ESO member states.
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8.
  • Ades, M., et al. (author)
  • Global Climate : in State of the climate in 2019
  • 2020
  • In: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 101:8, s. S17-S127
  • Journal article (peer-reviewed)
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9.
  • Ades, M., et al. (author)
  • GLOBAL CLIMATE
  • 2020
  • In: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY. - 0003-0007 .- 1520-0477. ; 101:8
  • Journal article (peer-reviewed)
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10.
  • Dareng, EO, et al. (author)
  • Polygenic risk modeling for prediction of epithelial ovarian cancer risk
  • 2022
  • In: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
  • Journal article (peer-reviewed)abstract
    • Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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  • Result 1-10 of 71
Type of publication
journal article (64)
conference paper (2)
research review (2)
Type of content
peer-reviewed (61)
other academic/artistic (7)
Author/Editor
Dennis, J (13)
Hamann, U (13)
Andrulis, IL (13)
Radice, P (13)
Couch, FJ (13)
Nevanlinna, H (13)
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Chenevix-Trench, G (13)
John, EM (13)
Antoniou, AC (13)
Offit, K. (13)
Peterlongo, P (12)
Manoukian, S (12)
Toland, AE (12)
Simard, J (12)
Schmutzler, RK (12)
McGuffog, L. (12)
Thomassen, M. (12)
Rantala, J. (12)
Montagna, M. (12)
Caligo, MA (12)
Godwin, AK (12)
Neuhausen, SL (12)
Tischkowitz, M (12)
Leslie, G (12)
Claes, KBM (12)
Easton, DF (11)
Stoppa-Lyonnet, D. (11)
Wappenschmidt, B. (11)
Engel, C. (11)
Barrowdale, D (11)
Diez, O (11)
Greene, MH (11)
Hulick, PJ (11)
Barnes, DR (11)
Friedman, E. (10)
Sharma, P. (10)
Miller, A (10)
Park, SK (10)
Hopper, JL (10)
Devilee, P (10)
Jakubowska, A (10)
Buys, SS (10)
Teixeira, MR (10)
Singer, CF (10)
Goldgar, DE (10)
Olah, E (10)
Osorio, A. (10)
Frost, D. (10)
Karlan, BY (10)
Loud, JT (10)
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University
Karolinska Institutet (34)
Lund University (17)
Uppsala University (16)
University of Gothenburg (14)
Chalmers University of Technology (9)
Stockholm University (3)
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Linnaeus University (3)
Umeå University (2)
Royal Institute of Technology (2)
Luleå University of Technology (1)
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Language
English (71)
Research subject (UKÄ/SCB)
Medical and Health Sciences (28)
Natural sciences (23)
Engineering and Technology (2)
Social Sciences (2)

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