1. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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2. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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3. |
- 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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4. |
- Falster, Daniel, et al.
(author)
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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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