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41,503 results for “taxonom”
Let the giants be named - Taxonomic description database for the isopod genus Bathynomus for the DELTA system
<p><span>Morphological characters have been extracted from recent relevant literature on <em>Bathynomus</em>, mainly from the six previously known species from the Atlantic Ocean and gulf of Mexico </span><span>(Magalhães and Young 2003; Lowry and Dempsey 2006; Shipley et al. 2016; Huang et al. 2022)</span><span>. To simultaneously maximize compactness and taxonomic value of the species description, mainly characters that have previously been interpreted as diagnostic at the species level have been included, omitting others which played no role in species delimitation. A taxonomic database has been newly set up using DELTA </span><span>(Dallwitz 1980, 1993; Dallwitz et al. 2006)</span><span>. Character states for all presently known Atlantic congeners have been scored to generate a natural language description and a new identification key </span><span>(Dallwitz 1974)</span><span> for the region as well as a species diagnosis. The species diagnosis has been composed based on the characters used in the identification key.</span></p> <p> </p>
Supporting Data - Taxonomic reassessment of Tetrapygus niger (Arbacioida, Echinoidea): molecular and morphological evidence support its placement in Arbacia
<p>This dataset contains the accession numbers and links of the sequences of the specimens analyzed by this work, other sequences used for the analyses can be found in the original article. The species from which the sequences were extracted are: Tetrapygus niger Molina, 1782; Arbacia dufresnii Blainville, 1825; Arbacia spatuligera Valenciennes, 1846 and Coelopleurus floridanus A. Agassiz, 1872. The accession numbers for the Cytochrome Oxidase subunit I (COI) and 28S of the nuclear genome are presented separately.</p><p>In addition, the morphological data of Tetrapygus niger (Test diameter, test height and peristome diameter) presented in this study are shown, as well as their collectors, corresponding collection, country and locality.</p>
Supporting Data for "Exploring ChatGPT-4 for Transforming Taxonomic Data into OWL: Lessons Learned and Implications for Ontology Development"
<p>Data from the trials with ChatGPT to generate OWL files for taxonomic data from the GBIF Backbone Taxonomy.</p> <p>Updates of version 2: additional prompts from the experiments with Gemini and DeepSeek.</p>
DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region
<p>This dataset has been prepared as part of the Interreg Alpine Space project Eco-AlpsWater (ASP569) - <em>Innovative Ecological Assessment and Water Management Strategy for the Protection of Ecosystem Services in Alpine Lakes and Rivers</em>, <a href="https://www.alpine-space.eu/projects/eco-alpswater/en/home">https://www.alpine-space.eu/projects/eco-alpswater/en/home</a></p> <p>Individual archives include 16S rRNA (cyanobacteria) and 18S rRNA (microalgae) FASTA sequences and associated blastn results obtained from the high throughput sequencing of plankton and biofilm bulk/eDNA samples collected in 2019 in 37 lakes and 22 rivers across the Alpine region. These are supporting files for the paper by Salmaso et al., 2022. DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region. Science of the Total Environment, in press.</p>
First genetic data for the Critically Endangered Cuban endemic Zapata Rail Cyanolimnas cerverai, and the taxonomic implications
<p>Data associated with the publication First genetic data for the Critically Endangered Cuban endemic Zapata Rail <em>Cyanolimnas cerverai</em>, and the taxonomic implications.</p>
Data and script: Reduced enumeration effort, but not coarse taxonomic resolution, is sufficient to represent beta diversity patterns of stream benthic diatoms
<p>This is a dataset on benthic diatom communities sampled in 90 riffles (the local communities) within nine near-pristine subtropical streams (each stream represented a metacommunity) in southeast subtropical Brazil. </p> <p>In addition to the dataset, we also provide the R code used to investigate whether reduced enumeration efforts (i.e., subsets of counted valves per sample) and the identification to the genus level are sufficient to recover patterns in the species composition and in beta diversity of benthic diatom metacommunities.</p>
njdowdy/tpt-taxonomy: TPT Taxonomic Resource v2.0.0
<p>This is the second public release of the taxonomic resources generated for the Terrestrial Parasite Tracker project. Some names given by list providers may be omitted due to being flagged for curatorial review for various reasons.</p>
EMA-amplicon-based taxonomic characterisation of the viable bacterial community present in untreated and SODIS treated roof-harvested rainwater
<p>Dataset for publication: EMA-amplicon-based taxonomic characterisation of the viable bacterial community present in untreated and SODIS treated roof-harvested rainwater, Strauss et al. (2018). DOI: 10.1039/c8ew00613j.</p>
Integrated Taxonomic Information System (ITIS): ITIS version 26 September 2023
ITIS provides authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. It is a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF). The ITIS and Species 2000 Catalogue of Life (CoL) partnership is proud to provide the taxonomic backbone to the Encyclopedia of Life (EOL). <p></p>https://www.itis.gov/
A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF)
<p>Publication date:<br> 2022-12-06T07:37:19-06:00</p> <p><br> A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF)<br> ---</p> <p>Global Biodiversity Information Facility (GBIF) facilitates access to billions of biodiversity data records. These records include detailed accounts of life on earth.</p> <p>To help records of specific life forms, GBIF provides a taxonomic backbone [1,2]. This backbone contains a long list of names used to describe species and associated hierarchies and taxonomic publications. These lists are sourced from datasets around the world.</p> <p>At time of writing (6 Dec 2022), GBIF publishes a simplified version of their taxonomic backbone at [https://hosted-datasets.gbif.org/datasets/backbone/](https://hosted-datasets.gbif.org/datasets/backbone/) [1].</p> <p>This repository provides script to pre-process https://hosted-datasets.gbif.org/datasets/backbone/current/simple.txt.gz to help facilitate access and improve performance of the creation of search indexes.</p> <p>Pre-process steps currently include:<br> 1. reducing amount of columns<br> 2. reverse sort by id<br> 3. reverse sort by name</p> <p><br> Contents<br> ---</p> <p>README:<br> this file</p> <p>repackage-gbif-backbone.sh:<br> script used to repackage GBIF Simple Backbone.</p> <p>repackage-gbif-backbone.log:<br> log of repackaging of GBIF Simple Backbone.</p> <p>backbone-current-simple.txt.gz:<br> original GBIF backbone archive</p> <p>gbif-backbone-by-name.tsv.gz:<br> two columns, gzipped, tab-separated text file with columns name, and id<br> reverse sorted by name </p> <p>gbif-backbone-by-name.tsv.sha256:<br> sha256 hash of the uncompressed gbif-backbone-by-name.tsv.gz</p> <p>gbif-backbone-by-id.tsv.gz:<br> 20 columns, gzipped, tab-separated text file with first 20 columns of repackaged GBIF backbone file<br> reverse sorted by id</p> <p>gbif-backbone-by-id.tsv.sha256:<br> sha256 hash of the uncompressed gbif-backbone-by-id.tsv.gz</p> <p>References<br> ---</p> <p>[1] Simplied GBIF Backbone Taxonomy. Accessed at https://hosted-datasets.gbif.org/datasets/backbone/ on 2022-12-06.<br> [2] GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2021-08-18.</p> <p><br> Hash URIs<br> ---<br> This publication includes the following content uris:</p> <p>hash://sha256/82d5f2153b4533322692d95eeb18b0f103e1b2297e38bd9ea935b07ba86cd7d5<br> hash://sha256/50c155f66efb2efba0b8b624f8541e81cbe16a701d420a5073791fb993f72919<br> hash://sha256/9cd7d4c91292d86c726210446cd6fe45602505a7c0ea3b7c4f4f481f85f193ad (uncompressed)<br> hash://sha256/f950dde25cce9ba9cce67caa1c68ce0c99cb31fe2dc9658fec85a987d9f31654<br> hash://sha256/f21c6b90f17c6083fcfb4853f3c581dcc2aadd291691fa128392a205321f420b (uncompressed)<br> hash://sha256/5e0a4d1d2d1cccbdcc6b2c9831fafe61c54eb055f2d13ec40d9ac161889b9f89<br> hash://sha256/f6e477133d0585706ee5522963b204200cb3cd198f011cbf62be0fa8519763b5 (uncompressed)<br> </p>
Planet Microbe Functional and Taxonomic annotation of Illumina WGS Prokaryotic Fraction for Semantic Web Analysis
<p>Functional and Taxonomic annotations computed from a subset of Illumina Whole-Genome Sequencing samples from the prokaryotic fraction of the <a href="https://www.planetmicrobe.org/">Planet Microbe</a> database. Data was computed using the pipeline available from https://github.com/hurwitzlab/planet-microbe-functional-annotation/, and post processing scripts from https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis. Files contain total annotation counts of Interpro, GO and NCBITaxon annotations, as well as additional sample metadata. See readme.txt file for more information.</p>
Supplementary file 1 from: Moliner Cachazo L, Makati K, Chadwick MA, Catford JA, Price BW, Mackay AW, Guiry MD, Murray-Hudson M, Murray-Hudson F (2023) A review of the freshwater diversity in the Okavango Delta and Lake Ngami (Botswana): taxonomic composition, ecology, comparison with similar systems and conservation status. Aquatic Sciences
<p>Dataset with 2,204 freshwater species from the Okavango Delta and Lake Ngami (Botswana), with additional 355 species found in other areas of Botswana that are likely to be present in the study region. The dataset covers the following groups: amphibians, birds, fishes, macroinvertebrates, macrophytes, mammals, reptiles, phytoplankton, and zooplankton. The following information is given for each species: status in the Okavango Delta and Lake Ngami (present/potentially present); conservation status globally, Phylum, Class, Order, Family, Genus, species name, cited synonyms, common name, habitat, presence in high water, presence in low water, ecology, distribution in continental Africa, confirmed locations in the Okavango Delta, site coordinates, references, notes.</p>
Metagenomes: metadata, taxonomic abundances, PlasX scores, circularity, and contig sequences
<p>This repository contains files that describe the ~36 million contigs that were assembled from 1,782 metagenomes</p> <p>metagenomes_contigs.tar.gz</p> <ul> <li>Fasta files of contig sequences. One file per metagenome</li> </ul> <p>metagenomes_metadata.txt</p> <ul> <li>Information about the 1,782 metagenomes</li> </ul> <p>metagenomes_taxonomic_abundances.txt.gz</p> <ul> <li>Taxonomic abundances in metagenomes, inferred by kraken2 and bracken</li> </ul> <p>metagenomes_contigs_summary.txt.gz</p> <ul> <li>PlasX scores</li> <li>Metagenomic coverage and detection</li> <li>Circularity</li> </ul>
18S rRNA V9 taxonomic classifier
<p>18S metabarcoding databases and naive-bayes classifier specific to the V9 region. Built from the <a href="https://pr2-database.org/">PR2 v5.0.0 database</a> using Qiime2 (version 2021.2).</p><p>Primers used:</p><p>1391f: GTACACACCGCCCGTC</p><p>EukBr: TGATCCTTCTGCAGGTTCACCTAC</p><p>File Description </p><p>pr2_seqs.qza |. Full length PR2 v5.0.0 sequences</p><p>pr2_tax.qza | Taxa for PR2 v5.0.0 database</p><p>refseqs_V9.qza. | Sequences for 18S V9 (primers 1391f, EukBrr), extracted from PR2 SSU v5.0.0, generated by qiime2-2021.2 (forward compatible)</p><p>classifier_V9.qza | Unweighted (uniform) naive-bayes classifier for 18S V9 extracted from PR2 SSU v5.0.0, generated by qiime2-2021.2 </p><p> </p>
Virus operational taxonomic units (vOTUs) from Stordalen Mire, Sweden
<p>This file is a collection of 5,051 virus operational taxonomy units (vOTUs) that were identified from samples collected from Stordalen Mire, a long-term ecological research site in Abisko, Sweden. Peat soil was sampled from the active layer across 3 different thaw stages (palsa, bog, and fen) between 2010-2017. From 379 bulk metagenomes, virus sequences were identified <em>in silico</em> using VirSorter1 (with additional stringent filtering criteria). Virus sequences above 5kb in length were then clustered into vOTUs (using a threshold of 95% identity and 80% coverage). This vOTU dataset is the basis of a research paper, entitled 'Virus ecology and 7-year temporal dynamics across a permafrost thaw gradient,' (Sun and Pratama, <em>et al.</em>, <em>in prep.</em>), which provides insights into permafrost viruses and their role in terrestrial carbon cycling.</p> <p> </p> <p>FUNDING:</p> <p>This research is a contribution of the EMERGE Biology Integration Institute (<a href="https://emerge-bii.github.io">https://emerge-bii.github.io/</a>), funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070.<br> We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.<br> This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632. DE-SC0010580. and DE-SC0016440.<br> A portion of this research was performed under the Facilities Integrating Collaborations for User Science (FICUS) program (proposal: 10.46936/10.25585/60001148) and used resources at the DOE Joint Genome Institute (<a href="https://www.google.com/url?q=https://ror.org/04xm1d337&sa=D&source=docs&ust=1674859614742521&usg=AOvVaw2XgXYw9eI4JIXRMKn3S9Se">https://ror.org/04xm1d337</a>) and the Environmental Molecular Sciences Laboratory (<a href="https://www.google.com/url?q=https://ror.org/04rc0xn13&sa=D&source=docs&ust=1674859614742655&usg=AOvVaw3UXdoHIFmVjc-mXUhDXYQt">https://ror.org/04rc0xn13</a>), which are DOE Office of Science User Facilities operated under Contract Nos. DE-AC02-05CH11231 (JGI) and DE-AC05-76RL01830 (EMSL).</p>
Environmental and taxonomic data along the Thames River - Lake St. Clair continuum in Ontario, August 2020 to September 2023.
Data for this research were collected from water samples obtained along the Thames River- Lake St. Clair continuum to determine differences in water quality and biodiversity between river and lake sites. Sampling began in Lake St. Clair in August of 2020 in Stoney Point Ontario. Samples were taken from the intake well of the water treatment plant. The intake pipe is located approximately 1km off-shore, at a depth of 1.9m. To address spatial differences, a second site was added in Lake St. Clair in Belle River, Ontario and a river site was added in Chatham, Ontario. Belle River samples were collected from the intake well at the water treatment plant, with the intake pipe located approximately 1km off-shore and at a depth of 3.1m. Chatham samples were collected from the surface of the Thames River as grab samples. Samples from both locations were collected weekly to monthly throughout June to October, 2021. To further increase spatial resolution, samples were collected from the mouth of the Thames River in Lighthouse Cove, Ontario, from June to October 2022, and from this site and another river site in Prairie Siding, Ontario, from June to October 2023. They were collected as grab samples from the surface of the water. Each site was sampled weekly to monthly.
Abundance of major taxonomic groups of invertebrates (arthropods and gastropods) collected with pitfall traps at four sites near Toolik Field Station Arctic LTER, Alaska in the summer of 2010.
Invertebrates (spiders, insects and slugs) were collected weekly using pitfall traps at four sites near the Arctic LTER at Toolik Field Station, Alaska. Traps were placed along transects in shrub (shrub-dominant) and open (tussock-dominant) tundra sites. Pitfall traps were placed for 48-hour intervals once per week from early June until mid-July 2010. Collected invertebrates were counted and identified to class (all invertebrates), order or family (for some of the most common families collected).
Abundance and biomass of major taxonomic groups of arthropods collected with pitfall and vacuum sampling in Arctic LTER plots fertilized for 24 years near Toolik Field Station, Alaska in the summer of 2013.
Arthropods (spiders and insects) were collected three times during the 2013 summer using pitfall traps and vacuum sampling in plots fertilized with Nitrogen and Phosphorus for 24 years, and in control plots, in an experiment established near Toolik Field Station, Alaska. Pitfall traps were placed for 48-hour intervals; vacuum samples were taken in a 1m2 area. Collected invertebrates were counted and identified to order or family.
Operational taxonomic units characterizing fungal communitties associated with resprouting Betula nana shrubs sampled across a fire-severity gradient in the Anaktuvuk River Fire burn scar, 2010
The dataset contains fungal community data from a sampling campaign in 2009, two growing seasons after the Anaktuvuk River Fire. We used molecular tools, including ARISA and fungal ITS sequencing, to characterize the mycorrhizal communities on resprouting Betula nana shrubs across a fire-severity gradient. Summarized data can be viewed by site and provide information on richness and abundance of basidiomycetes and ascomycetes andChao1 and MaoTau estimators of richness. OTU data are provided for each shrub sampled in the study.
Abundance and biovolume of taxonomically-resolved phytoplankton and microzooplankton imaged continuously underway with an Imaging FlowCytobot along the NES-LTER Transect in winter 2018
These data represent the abundance and biovolume of taxonomically-resolved phytoplankton and microzooplankton imaged continuously underway along the NES-LTER Transect during cruise EN608 in winter 2018. Images were obtained with an Imaging FlowCytobot (IFCB) sampling at approximately 20-min intervals from seawater supplied from 5 meters water depth. Data are provided for the subset of images during the cruise that were on the north-south transect along longitude 70 53’ W. Sizes for individuals were determined automatically by image processing, while identifications to morphological categories were done manually. Data are provided by taxon with names and machine-readable identifiers matched to the lowest taxonomic level to the World Register of Marine Species. Two data tables are provided: the level 1b for each occurrence and the level 2 that summarizes the occurrences by taxon per sample. Individual and sample identifiers are linked to images served by an external repository. This data package provides 144,281 machine-readable occurrences for incorporation into the Ocean Biogeographic Information System and the Global Ocean Observing System Essential Ocean Variables Phytoplankton biomass and diversity and the microplankton size class of Zooplankton biomass and diversity.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.