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52 results for “plant detection”
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
<p>In the last decade, High-Throughput Sequencing (HTS) has revolutionized biology and medicine. This technology allows the sequencing of huge amount of DNA and RNA fragments at a very low price. In medicine, HTS tests for disease diagnostics are already brought into routine practice. However, the adoption in plant health diagnostics is still limited. One of the main bottlenecks is the lack of expertise and consensus on the standardization of the data analysis. The Plant Health Bioinformatic Network (PHBN) is an Euphresco project aiming to build a community network of bioinformaticians/computational biologists working in plant health. One of the main goals of the project is to develop reference datasets that can be used for validation of bioinformatics pipelines and for standardization purposes.</p> <p>Semi-artificial datasets have been created for this purpose (Datasets 1 to 10). They are composed of a "real" HTS dataset spiked with artificial viral reads. It will allow researchers to adjust their pipeline/parameters as good as possible to approximate the actual viral composition of the semi-artificial datasets. Each semi-artificial dataset allows to test one or several limitations that could prevent virus detection or a correct virus identification from HTS data (<i>i.e.</i> low viral concentration, new viral species, non-complete genome).</p> <p>Eight artificial datasets only composed of viral reads (no background data) have also been created (Datasets 11 to 18). Each dataset consists of a mix of several isolates from the same viral species showing different frequencies. The viral species were selected to be as divergent as possible. These datasets can be used to test haplotype reconstruction software, the goal being to reconstruct all the isolates present in a dataset.</p> <p><span>A GitLab repository (<a href="https://gitlab.com/ilvo/VIROMOCKchallenge">https://gitlab.com/ilvo/VIROMOCKchallenge</a>) is available and provides a complete description of the composition of each dataset, the methods used to create them and their goals.</span></p>
Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata
<p>Genetic and Environmental datasets used to perform population structure, isolation-by-distance, and GLMM analysis. See the paper for abbreviations and units of DEM-derived variables.</p>
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
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Data from: The effect of plant identity and mixed feeding on the detection of seed DNA in regurgitates of carabid beetles
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Detection of new pathways involved in the acceptance and the utilization of plant-based diet in isogenic lines of rainbow trout fry
GEO Series GSE92673. Oncorhynchus mykiss. 34 samples. Type: Expression profiling by array.
Detection of plant microRNAs in EVOO and plasma samples of healthy volunteers 2 hours postingestion of 40 mL of EVOO.
GEO Series GSE76735. Olea europaea; Homo sapiens. 2 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Detecting shifts in the mode of chromosomal speciation across the cosmopolitan plant lineage Carex
<p>Data and code for the manuscript "Detecting shifts in the mode of chromosomal speciation across the cosmopolitan plant lineage <em>Carex</em>". </p>
Plant Viroid Detection Microarray
GEO Series GSE44334. Columnea latent viroid; Citrus dwarfing viroid; Elaviroid; Potato spindle tuber viroid; Peach latent mosaic viroid; Apscaviroid cicatricimali; Avocado sunblotch viroid; Chrysanthemum stunt viroid; Hop latent viroid; Chrysanthemum chlorotic mottle viroid; Hostuviroid; Pospiviroid; Cocadviroid; Apscaviroid; Coleviroid; Hop stunt viroid; Avsunviroid; unclassified viroids; Tomato apical stunt viroid; Tomato planta macho viroid; Citrus exocortis viroid; Pelamoviroid; Coleus blumei viroid 1. 20 samples. Type: Other.
Detection of plant microRNAs in edible-plant based products
GEO Series GSE234786. Solanum lycopersicum; Olea europaea; Pyrus communis; Citrus sinensis; Prunus dulcis; Juglans regia; Spinacia oleracea; Malus domestica. 8 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Plant virus detection microarray
GEO Series GSE15837. Sobemovirus; Southern bean mosaic virus; Tomato ringspot virus; Cucumovirus; Potyvirus; Tobamovirus; Tobacco mosaic virus; Ilarvirus; unidentified; Zinnia elegans; Orthotospovirus; Orthotospovirus tomatomaculae; Potexvirus; Potato virus X; Plum pox virus; Carlavirus; Capillovirus; Tobacco ringspot virus; Comovirus; Bean pod mottle virus; Nepovirus; Arabis mosaic virus; Tobravirus; Prunus necrotic ringspot virus; Taraxacum officinale; Pomovirus. 17 samples. Type: Expression profiling by array.
Evaluation of Target Preparation Methods for Single-Feature Polymorphism Detection in Large Complex Plant Genomes
GEO Series GSE12770. Zea mays. 36 samples. Type: Other.
Apple images for plant disease detection
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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.