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DNA/RNA sequences, gene expression, protein structures, metagenomics, single-cell sequencing
27,613 datasets
Victoria, British Columbia, is analyzed for changes in buildings, roads, and forest cover using satellite imagery from the 2000s, 2010s, and 2020s. Natural Resources Canada produced this dataset by intersecting GeoAI-extracted features with Statistics Canada's Open Database of Buildings and National Roads Network. The analysis enables tracking of urban development and environmental changes over time.
Natural England's 2021 dataset categorizes land in Northumberland, Durham, Tyne & Wear, and Tees Valley into four risk zones for great crested newt conservation. Red zones contain regionally or nationally important populations, including designated Sites of Special Scientific Interest, while amber and green zones represent main population centers and sparse distributions, respectively. The data is derived from multiple sources including land cover maps, Ordnance Survey data, and freshwater habitat monitoring.
Geospatial zones categorizing the distribution and development impact risk for great crested newts in Somerset, UK. The dataset is produced by Natural England and Somerset County Council, with data from 2022 and underlying sources from 2007-2020. It classifies areas into red, amber, green, and white zones based on population importance and habitat connectivity.
North Somerset and South Gloucestershire areas are categorized into risk zones for great crested newt (GCN) conservation. The dataset, created by Natural England in 2022, defines red, amber, green, and white zones based on GCN population importance and development impact. It incorporates data from multiple sources including Ordnance Survey, the Rural Payments Agency, and local environmental records centres.
A geospatial dataset from Natural England categorizes areas in Essex, UK, based on the distribution and conservation risk to great crested newts. It defines four risk zones—red, amber, green, and white—based on population importance and habitat connectivity. The dataset is derived from multiple sources including Natural England, Ordnance Survey, and the Freshwater Habitats Trust, with a last update timestamp of 2026-07-13.
Natural England's 2021 dataset categorizes areas in Cumbria, UK, into four zones based on great crested newt occurrence and development impact risk. Red zones contain key populations on a regional, national, or international scale, including designated Sites of Special Scientific Interest. The data is derived from multiple sources including Ordnance Survey, LCM land cover maps, and PondNet monitoring.
Central African Republic building footprints are derived from OpenStreetMap, where every feature is tagged with `building=*`. The data includes structures from residential homes to hospitals, schools, and places of worship. It was last updated on 2026-06-20 by the Humanitarian OpenStreetMap Team (HOT).
OpenStreetMap volunteer mappers have contributed building footprint data across Cameroon, tagged for various uses from residential homes to hospitals and schools. Coverage is likely more complete in urban areas where mappers are active, while remote areas may be sparse. The Humanitarian OpenStreetMap Team (HOT) provides this data under an ODbL license, last updated in June 2026.
526 Gbp of high-fidelity reads were assembled and scaffolded with Hi-C data to produce a haplotype-collapsed genome assembly for the durum wheat variety 'Kronos'. The resulting 14 scaffolds, each greater than 600 Mbp, represent the 14 chromosomes of this tetraploid wheat (7 x AB). An updated long non-coding RNA (lncRNA) annotation (v1.1) is included, where 150 outlier genes were filtered out.
Alvaro Barbeira's sample archive provides the necessary components to impute GWAS summary statistics for integration with PrediXcan MASHR-M models from the GTEx v8 project. Its contents include a 1000 Genomes reference panel in hg38, precomputed LD regions, and coordinate mapping tables for harmonizing genomic assemblies. This dataset is designed as a tutorial resource for performing transcriptome-wide association studies.
114 publicly available GWAS traits harmonized and imputed to the GTEx v8 variant reference. The dataset includes metadata on traits, publication links, consortia, sample sizes, and population ancestry. It was prepared by Alvaro Barbeira at the University of Chicago.
114 GWAS traits were harmonized and imputed to GTEx v8 variants using only European samples. This package contains results from several GWAS-QTL integration methods, including colocalization, prediction models, SMR, S-MultiXcan, and S-PrediXcan, as analyzed in a related preprint. The data was produced by Alvaro Barbeira at the University of Chicago.
2048 x 2048 pixel high-quality images of kidney tissue and a calibration grid, paired with 1024x1024 motion-blurred counterparts, were collected using a MiniTEM microscope. The dataset, created by Håkan Wieslander of Uppsala University, includes raw files and a partitioned set for training, validation, and testing. Five registered low-quality images are cropped and aligned to each high-quality image.
Pre-trained convolutional neural network models for predicting Tn5 transposase insertion bias from local DNA sequence context. The data includes genome-wide bias predictions for multiple reference genomes (hg38, hg19, mm10, etc.), dispersion models for footprinting, and transcription factor binding prediction models. Yan Hu from Harvard University Press released this data associated with the multi-scale footprinting project.
Lindsay Katz from the University of Toronto created this database of Australian Parliamentary Debates. It contains proceedings from each sitting day in the House of Representatives from 02 March 1998 to 31 July 2025, parsed from official XML Hansard transcripts. The data includes standardized party and electorate information, with improved flagging for questions, answers, and interjections.
Department for Work and Pensions National Statistics on Housing Benefit overpayments and fraud volumes. The data contains aggregate-level statistics received quarterly from each UK Local Authority. Note that from April 2016, the statistics no longer include fraud data.
Australian Ocean Data Network provides satellite-derived measurements of the diffuse attenuation coefficient at 490nm wavelength (Kd490), which indicates light penetration in the ocean. The data is produced from the VIIRS sensor aboard the SNPP satellite platform using a semi-empirical model based on water-leaving radiance ratios. The dataset was last updated on 2026-07-13.
One-minute averaged observations of sea surface properties from the Southern Ocean Flux Station (SOFS) mooring. The data includes meteorological parameters, downwelling radiation, and sea water temperature and salinity, collected to study heat, moisture, energy, and CO2 transfer between the atmosphere and ocean. The mooring is operated by the Australian Ocean Data Network and was first deployed at 46.7S, 142E in March 2010.
OpenStreetMap building footprints across Niger, tagged for residential, commercial, and institutional uses. The Humanitarian OpenStreetMap Team (HOT) provides this data, last updated on 2026-06-19. Coverage reflects volunteer mapper activity, with urban areas typically well-represented and remote areas potentially sparse.
OpenStreetMap-derived building footprints tagged across Mozambique, including residential, hospital, school, and religious structures. Coverage reflects volunteer mapper activity, with urban areas likely well-represented and remote areas potentially sparse. The data is maintained by the Humanitarian OpenStreetMap Team and was last updated in June 2026.