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79 results for “plant database”
Database for meta-analysis of herbivore impacts on plant-soil feedbacks
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Data from: Mining microsatellite markers from public expressed sequence tags databases for the study of threatened plants
Background: Simple Sequence Repeats (SSRs) are widely used in population genetic studies but their classical development is costly and time-consuming. The ever-increasing available DNA datasets generated by high-throughput techniques offer an inexpensive alternative for SSRs discovery. Expressed Sequence Tags (ESTs) have been widely used as SSR source for plants of economic relevance but their application to non-model species is still modest. Methods: Here, we explored the use of publicly available ESTs (GenBank at the National Center for Biotechnology Information-NCBI) for SSRs development in non-model plants, focusing on genera listed by the International Union for the Conservation of Nature (IUCN). We also search two model genera with fully annotated genomes for EST-SSRs, Arabidopsis and Oryza, and used them as controls for genome distribution analyses. Overall, we downloaded 16 031 555 sequences for 258 plant genera which were mined for SSRsand their primers with the help of QDD1. Genome distribution analyses in Oryza and Arabidopsis were done by blasting the sequences with SSR against the Oryza sativa and Arabidopsis thaliana reference genomes implemented in the Basal Local Alignment Tool (BLAST) of the NCBI website. Finally, we performed an empirical test to determine the performance of our EST-SSRs in a few individuals from four species of two eudicot genera, Trifolium and Centaurea. Results: We explored a total of 14 498 726 EST sequences from the dbEST database (NCBI) in 257 plant genera from the IUCN Red List. We identify a very large number (17 102) of ready-to-test EST-SSRs in most plant genera (193) at no cost. Overall, dinucleotide and trinucleotide repeats were the prevalent types but the abundance of the various types of repeat differed between taxonomic groups. Control genomes revealed that trinucleotide repeats were mostly located in coding regions while dinucleotide repeats were largely associated with untranslated regions. Our results from the empirical test revealed considerable amplification success and transferability between congenerics. Conclusions: The present work represents the first large-scale study developing SSRs by utilizing publicly accessible EST databases in threatened plants. Here we provide a very large number of ready-to-test EST-SSR (17 102) for 193 genera. The cross-species transferability suggests that the number of possible target species would be large. Since trinucleotide repeats are abundant and mainly linked to exons they might be useful in evolutionary and conservation studies. Altogether, our study highly supports the use of EST databases as an extremely affordable and fast alternative for SSR developing in threatened plants.
USDA NRCS PLANTS Database: USDA PLANTS images DwCA
<p>The PLANTS Database, https://plants.usda.gov/ provides standardized information about the vascular plants, mosses, liverworts, hornworts, and lichens of the U.S. and its territories. It includes names, plant symbols, checklists, distributional data, species abstracts, characteristics, images, crop information, automated tools, onward Web links, and references. This information primarily promotes land conservation in the United States and its territories, but academic, educational, and general use is encouraged. PLANTS reduces government spending by minimizing duplication and making information exchange possible across agencies and disciplines. Data published on EOL by the PLANTS database include attribute data, images and descriptive text.</p> <p>This is primarily an image resource.</p> <p> </p> <p>Captured data during API bulk updates: {"United States Department of Agriculture":{"ror":"01na82s61","isni":"0000 0004 0478 6311"}}</p>
Text-fig. 2. "Site screen" scheme of complete results of the IPR-vegetation analysis derived from the database. in The Integrated Plant Record Vegetation Analysis: Internet Platform And Online Application
Text-fig. 2. "Site screen" scheme of complete results of the IPR-vegetation analysis derived from the database.
Linked collectors and determiners for: Florabank1 - A grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region).
Natural history specimen data linked to collectors and determiners held within, "Florabank1 - A grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/271c444f-f8d8-4986-b748-e7367755c0c1">https://bionomia.net/dataset/271c444f-f8d8-4986-b748-e7367755c0c1</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/271c444f-f8d8-4986-b748-e7367755c0c1">https://gbif.org/dataset/271c444f-f8d8-4986-b748-e7367755c0c1</a>. Formatted as a Frictionless Data package.
Figure 3 from: Desmet P, Brouilet L (2013) Database of Vascular Plants of Canada (VASCAN): a community contributed taxonomic checklist of all vascular plants of Canada, Saint Pierre and Miquelon, and Greenland. PhytoKeys 25: 55-67. https://doi.org/10.3897/phytokeys.25.3100
Figure 3 - The VASCAN Darwin Core Archive, structured following the GBIF GNA Profile. It is a compressed folder containing 4 text files with tab-seperated values and 2 xml files. Taxon and scientific name information is provided in taxon.txt, with one record for each taxon and child-parent-relationships representing the classification. Records in the extension files distribution.txt, vernacularname.txt and description.txt have a many-to-one relation with the records in taxon.txt and provide additional information for each taxon. The archive structure and term definitions are described in meta.xml. The dataset metadata are provided in eml.xml.
Figure 2 from: Desmet P, Brouilet L (2013) Database of Vascular Plants of Canada (VASCAN): a community contributed taxonomic checklist of all vascular plants of Canada, Saint Pierre and Miquelon, and Greenland. PhytoKeys 25: 55-67. https://doi.org/10.3897/phytokeys.25.3100
Figure 2 - Regional distribution of accepted species from the Database of Vascular Plants of Canada (VASCAN). For each region, the number of native, introduced and ephemeral species is shown, i.e. species with a confirmed presence in the region. The regions are ordered by total number of species.
Figure 1 from: Desmet P, Brouilet L (2013) Database of Vascular Plants of Canada (VASCAN): a community contributed taxonomic checklist of all vascular plants of Canada, Saint Pierre and Miquelon, and Greenland. PhytoKeys 25: 55-67. https://doi.org/10.3897/phytokeys.25.3100
Figure 1 - Taxonomic distribution of accepted species per family from the Database of Vascular Plants of Canada (VASCAN). The families are ordered by total number of species. Families with less than 80 species are grouped in 'Other families'.
Figure 3 from: Brosens D, Van Landuyt W, Vanhecke L (2012) Florabank1: a grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region). PhytoKeys 12: 59-67. https://doi.org/10.3897/phytokeys.12.2849
Figure 3 - Number of prospected 1 km? grids in each grid of 4?4 km for the period 1972-2004. A 1 km? grid cell is considered as prospected if at least 90 species have been recorded.
Figure 2 from: Brosens D, Van Landuyt W, Vanhecke L (2012) Florabank1: a grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region). PhytoKeys 12: 59-67. https://doi.org/10.3897/phytokeys.12.2849
Figure 2 - Number of prospected 1 km? grids in each grid of 4?4 km for the period 1939–1971. A 1 km? grid cell is considered as prospected if at least 90 species have been recorded.
Figure 2 from: Dauby G, Zaiss R, Blach-Overgaard A, Catarino L, Damen T, Deblauwe V, Dessein S, Dransfield J, Droissart V, Duarte MC, Engledow H, Fadeur G, Figueira R, Gereau RE, Hardy OJ, Harris DJ, de Heij J, Janssens S, Klomberg Y, Ley AC, Mackinder BA, Meerts P, van de Poel JL, Sonké B, Sosef MSM, Stévart T, Stoffelen P, Svenning J-C, Sepulchre P, van der Burgt X, Wieringa JJ, Couvreur TLP (2016) RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74: 1-18. https://doi.org/10.3897/phytokeys.74.9723
Figure 2 - Examples of the georeferencing verification process. a The georeferenced record falls within a neighbouring country (here Gabon - GAB) of its documented country (here Republic of the Congo - COG). The nearest distance between the occurrence and the border of the documented country is computed b The georeferenced record falls within a non-neighbouring country (here Equatorial Guinea - GNQ) of its documented country (here Republic of the Congo). This record is classified as 'Error' and is discarded c The georeferenced record lies beyond the coastline. The nearest distance between the occurrence and the coastline of the documented country is computed.
Figure 1 from: Dauby G, Zaiss R, Blach-Overgaard A, Catarino L, Damen T, Deblauwe V, Dessein S, Dransfield J, Droissart V, Duarte MC, Engledow H, Fadeur G, Figueira R, Gereau RE, Hardy OJ, Harris DJ, de Heij J, Janssens S, Klomberg Y, Ley AC, Mackinder BA, Meerts P, van de Poel JL, Sonké B, Sosef MSM, Stévart T, Stoffelen P, Svenning J-C, Sepulchre P, van der Burgt X, Wieringa JJ, Couvreur TLP (2016) RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74: 1-18. https://doi.org/10.3897/phytokeys.74.9723
Figure 1 - Left map: record density in 2° × 2°cell including all georeferenced records that passed the quality checks. This map includes records that are identified or not to species level. Right map: main extent of RAINBIO geographical coverage from south of Sahel and north of Southern Africa (grey area); extent of tropical rain forest regions adapted from the land cover map published by Mayaux et al. (2004) (green area).
Figure 3 from: Dauby G, Zaiss R, Blach-Overgaard A, Catarino L, Damen T, Deblauwe V, Dessein S, Dransfield J, Droissart V, Duarte MC, Engledow H, Fadeur G, Figueira R, Gereau RE, Hardy OJ, Harris DJ, de Heij J, Janssens S, Klomberg Y, Ley AC, Mackinder BA, Meerts P, van de Poel JL, Sonké B, Sosef MSM, Stévart T, Stoffelen P, Svenning J-C, Sepulchre P, van der Burgt X, Wieringa JJ, Couvreur TLP (2016) RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74: 1-18. https://doi.org/10.3897/phytokeys.74.9723
Figure 3 - Most represented families (sorted by number of records) for each of the three divisions of vascular plants represented in the RAINBIO database. A Magnoliophyta B Gymnosperms C Pteridophyta.
Data from: Mining microsatellite markers from public expressed sequence tags databases for the study of threatened plants
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Database for spring, summer and fall-planted cover crop performance across the state of Nebraska
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A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011
This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.
Reproductive and vegetative phenology database of two progenies of Euterpe oleracea Mart. planted in the Amazon estuary
<p><span>During the period from May/2009 to April/2013, we monitored the reproductive and vegetative phenophases of two progenies of <em>Euterpe oleracea</em> Mart., planted in the floodplain forest of the Amazon estuary. We carried out prospecting on the east and west coast of the Amazon estuary with the aim of selecting native açaí palm matrices with phenotypic production characteristics during the period of low natural production of this palm.</span></p>
Figure 1 from: Brosens D, Van Landuyt W, Vanhecke L (2012) Florabank1: a grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region). PhytoKeys 12: 59-67. https://doi.org/10.3897/phytokeys.12.2849
Figure 1 - Taxonomic coverage of Florabank1
Database of thermal power plant of YASSA-DIBAMBA CAMEROUN (2017-2018-2019-2020-2021)
<p>In this work, genetic algorithm coupled with neural networks was used to predict the concentration of pollutants in the Yassa area. The model takes into account the meteorological parameters of the study area and the source over 5 years, period from January 2017 to December 2021. To evaluate the model, two indices are used to indicate the prediction model’s performance; the Squared Correlation Coefficient R<sup>2</sup> whose value in the test case is 0.9996 and the Mean Square Error (MSE) whose best value is 0.0044756. We also evaluated the optimization methods and found that compared to the swarm by particle optimization, the genetic algorithm gives a better “fitness function curve” as a function of the number of iterations. The results showed that the GA-ANN coupling presented here is able to provide a reliable and accurate prediction of the distance of the area where the air quality standards and criteria are met. The safe distance where thermal power plant activity respects the air quality criteria is beyond 2200m. The results help not only in the choice of the location of the thermal power plant but also in the monitoring of the air quality in residential areas.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.