1. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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2. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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3. |
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4. |
- Abdesselam, A., et al.
(author)
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The barrel modules of the ATLAS semiconductor tracker
- 2006
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In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 568:2, s. 642-671
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Journal article (peer-reviewed)abstract
- This paper describes the silicon microstrip modules in the barrel section of the SemiConductor Tracker (SCT) of the ATLAS experiment at the CERN Large Hadron Collider (LHC). The module requirements, components and assembly techniques are given, as well as first results of the module performance on the fully assembled barrels that make up the detector being installed in the ATLAS experiment.
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5. |
- Falster, Daniel, et al.
(author)
-
AusTraits, a curated plant trait database for the Australian flora
- 2021
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In: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
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6. |
- Hakkaart, C, et al.
(author)
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Copy number variants as modifiers of breast cancer risk for BRCA1/BRCA2 pathogenic variant carriers
- 2022
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In: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 5:1, s. 1061-
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Journal article (peer-reviewed)abstract
- The contribution of germline copy number variants (CNVs) to risk of developing cancer in individuals with pathogenic BRCA1 or BRCA2 variants remains relatively unknown. We conducted the largest genome-wide analysis of CNVs in 15,342 BRCA1 and 10,740 BRCA2 pathogenic variant carriers. We used these results to prioritise a candidate breast cancer risk-modifier gene for laboratory analysis and biological validation. Notably, the HR for deletions in BRCA1 suggested an elevated breast cancer risk estimate (hazard ratio (HR) = 1.21), 95% confidence interval (95% CI = 1.09–1.35) compared with non-CNV pathogenic variants. In contrast, deletions overlapping SULT1A1 suggested a decreased breast cancer risk (HR = 0.73, 95% CI 0.59-0.91) in BRCA1 pathogenic variant carriers. Functional analyses of SULT1A1 showed that reduced mRNA expression in pathogenic BRCA1 variant cells was associated with reduced cellular proliferation and reduced DNA damage after treatment with DNA damaging agents. These data provide evidence that deleterious variants in BRCA1 plus SULT1A1 deletions contribute to variable breast cancer risk in BRCA1 carriers.
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7. |
- Meyer, Peter A., et al.
(author)
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Data publication with the structural biology data grid supports live analysis
- 2016
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Journal article (peer-reviewed)abstract
- Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data. sbgrid. org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.
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8. |
- Gross, O, et al.
(author)
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Stem cell therapy for Alport syndrome: the hope beyond the hype
- 2009
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In: Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association. - : Oxford University Press (OUP). - 1460-2385. ; 24:3, s. 731-734
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Journal article (peer-reviewed)
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