AndreaBozzo/ceres-open-data-index huggingface dataset:
MTGSAM: Multiple-Trait Gibbs Sampler for Animal Models

<p>A set of FORTRAN programs to implement a multiple-trait Gibbs sampling algorithm for (co)variance component inference in animal models (MTGSAM) was developed. The MTGSAM programs are available to the public. The programs support models with correlated genetic effects and arbitrary numbers of covariates, fixed effects, and independent random effects for each trait. Any combination of missing traits is allowed. The programs were used to estimate variance components for 50 replicates of simulated data. Each replicate consisted of 50 animals of each sex in each of four generations, for 400 animals in each replicate for two traits. For MTGSAM, informative prior distributions for variance components were inverted Wishart random variables with 10 df and means equal to the simulation parameters. A total of 15,000 Gibbs sampling rounds were completed for each replicate, with 2,000 rounds discarded for burn-in. For multiple-trait derivative free restricted maximum likelihood (MTDFREML), starting values for the variance components were the simulation parameters. Averages of posterior mean of variance components estimated using MTGSAM with informative and flat prior distributions for variance components and REML estimates obtained using MTDFREML indicated that all three methods were empirically unbiased. Correlations between estimates from MTGSAM using flat priors and MTDFREML all exceeded .99. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: MTGSAM: Multiple-Trait Gibbs Sampler for Animal Models.</p> <p>File Name: Web Page, url: <a href="https://aipl.arsusda.gov/software/mtgsam/mtdgsam.html">https://aipl.arsusda.gov/software/mtgsam/mtdgsam.html</a> </p><p>download and information page</p></li></ul><p></p>

Tags: algorithms, animal-models, animals, computer-software, covariance, models, statistical-analysis, variance
Organization: Department of Agriculture
Varroa Pop

<p>Varroa Pop simulates the growth of Varroa mite population in honey bee colonies. The program demonstratres how Varroa mites influence colony population growth throughout the year. You can change many factors through the menus in the model such as the initial population size, queen egg laying potential, and mite reproduction rates, so you can see how these factors influence both colony and mite population growth. We hope that the model will help you understand the interactions between the honey bee and mite populations and provide insights on how best to control Varroa in colonies. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Varroa Pop download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=75&modecode=20-22-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=75&modecode=20-22-05-00</a> </p></li></ul><p></p>

Tags: honey-bee-colonies, honey-bees, menu-planning, mites, models, natural-resources-earth-and-environmental-sciences, oviposition, population-growth, population-size, reproduction, varroa
Organization: Department of Agriculture
GRACEnet Soil Biology Network

<p>To help enhance USA soil health, and ensure a robust living soil component that sustains essential functions for healthy plants, animals, and environment, and ultimately provides food for a healthy society, the GRACEnet Soil Biology group are working together with the larger USDA-ARS GRACEnet community to provide soil biology component measurements across regions and to eliminate data gaps for GRACEnet and REAP efforts. The Soil Biology group is focused on efforts that foster method comparison and meta-analyses to allow researchers to better assess soil biology and soil health indicators that are most responsive to agricultural management and that reflect the ecosystems services associated with a healthy, functioning soil.</p>
<p>The GRACEnet Soil Biology mission is to produce the soil biology data, including methods of identifying and quantifying specific organisms and processes they govern, that are needed to evaluate impacts on agroecosystems and sustainable agricultural practices. This data collection effort is being accomplished in a highly structured manner to support current and future soil health and antimicrobial resistance research initiatives. The outcomes of the efforts of this team will provide a common biological data platform for several ARS databases, including: GRACEnet/REAP, Nutrient Use and Outcome Network (NUOnet), Long-Term Agroecosystem Research (LTAR) network, soil biology (e.g., MyPhyloDB) databases, and others.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Soil Biology Data Search.</p> <p>File Name: Web Page, url: <a href="https://agcros-usdaars.opendata.arcgis.com/datasets?group_ids=091b86e9e44a4e948ef2aeae3c916ca5" target="_blank">https://agcros-usdaars.opendata.arcgis.com/datasets?group_ids=091b86e9e44a4e948ef2aeae3c916ca5</a> </p></li></ul>

Tags: agricultural-research-service, ars, data-gov, national-program-211, national-program-212, natural-resource-and-genomics-data-systems, np211, np212, online-database, soil-biology, soil-health-and-resiliency
Organization: Department of Agriculture
ExtractChem

<p>This program is developed to predict the major ion, B composition, electrical conductivity (EC) and osmotic pressure (OP) of a soil solution at a desired water content based on the known ion composition at another water content.</p>
<p>The major uses of the model are envisioned as:
Obtaining a predicted saturation extract composition, EC and OP based on analysis of a 1:1, 1:2 or 1:5 soil water extract.
Correction of the soil water extract data for gypsiferous soils when calibrating field electromagnetic or electrical resistivity surveys for salinity.
Calculating UNSATCHEM or other chemical transport model input soil water concentrations at a specific pressure head (and thus water content) based on analyses of soil extracts.
Basis of the model</p>
<p>The program is based on the chemical routines used in the UNSATCHEM model (Suarez and Simunek, 1996, 1997). It considers major ions, boron, and the chemical processes of cation exchange, precipitation-dissolution of calcite and gypsum, and boron adsorption using the constant capacitance model.</p>
<p>The model can be run in batch mode or in individual cases with display to the screen. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: ExtractChem download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=155&modecode=20-36-15-00">https://www.ars.usda.gov/research/software/download/?softwareid=155&modecode=20-36-15-00</a> </p></li></ul><p></p>

Tags: adsorption, boron, calcite, capacitance, cation-exchange, electrical-conductivity, electrical-resistance, gypsiferous-soils, gypsum, ions, models, osmotic-pressure, salinity, soil-solution, soil-water, surveys, water-content
Organization: Department of Agriculture
Cattle and Sheep Whole Genome Sequence (WGS)

<p>Cattle and Sheep Whole Genome Sequence (WGS)</p>
<p>USMARC Beef Cattle Diversity Panel (MBCDPv2.9)</p>
<ul>
<li>Finished 14x WGS of 96 sires from 19 beef breeds representing >99% of the germplasm used in the US beef industry Article for cattle producers </li>
<li>USMARC Extended Cattle Diversity Panel (MECDPv1.0)</li>
<li>Ongoing 10x WGS from 46 breeds, includes MBCDPv2.9 sires plus four animals from each of 27 additional breeds </li>
<li>USMARC Sheep Diversity Panel (MSDPv2.4)</li>
<li>Finished 16x WGS of 96 rams from 10 US sheep breeds representing diversity in traits like fertility, growth, and longevity.</li>
<li>USMARC Extended Sheep Diversity Panel (MESDPv1.0)</li>
<li>Ongoing 10x WGS from 15 breeds, includes MSDPv2.4 rams plus 10 animals from each of 5 additional breeds </li>
<li>Related species (mapped to cattle and/or sheep)</li>
<li>Ongoing 10x WGS from related species like gaur, bison, banteng, and yak.</li>
<li>Livestock Cell Lines (mapped to cattle and/or sheep)</li>
<li>
<p>Ongoing 10x WGS from cell lines used in USMARC research like Madin-Darby Bovine Kidney (MDBK) cells.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Cattle and Sheep Whole Genome Sequence (WGS).</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/plains-area/clay-center-ne/marc/wgs/main/" target="_blank">https://www.ars.usda.gov/plains-area/clay-center-ne/marc/wgs/main/</a> </p></li></ul>
</li>
</ul>

Tags: ars, data-gov, np101
Organization: Department of Agriculture
β-Cyclodextrin nano-encapsulated carvacrol inclusion complexes improve postharvest quality of limes (<i>Citrus latifolia</i> Tanaka)

<p dir="ltr">Carvacrol was encapsulated by β-cyclodextrin, and spray dried by the nano s pray dryer B-90. The nanoparticle was applied as a sachet to preserve limes. The data set contains the physical and chemical properties of the nanoparticles, including encapsulation efficiency, Fourier transform infrared information , release profile, particle diameter, antimicrobial activity, and antioxidant activity. The nanoparticles were applied to preserve postharvest limes; fruit firmness, soluble solid content, titratable acid, weight loss, peel color change, and microbial count were shown in the data set. The data set provides evidence of nanoparticles preserving and extending the shelf life of postharvest fruit.</p>

Tags: encapsulation, fruit-preservation-effect, nano-spray-drying, plant-essential-oils-eos
Organization: Department of Agriculture
Data from: Impact of Ivermectin on the Gut Microbial Ecosystem

<p dir="ltr">The SHIME® (Simulator of the Human Intestinal Microbial Ecology) was used for in vitro cultivation of the human gut microbiota (3 donors) prior to and following the addition of ivermectin to the system.  These additions were performed on bioreactors which had stabilized on a background of media supplemented with either soluble or insoluble fiber or no addition controls. Data collected include 16S rRNA gene amplicon sequencing and short chain fatty acid (SCFA) concentrations.</p>

Tags: 16s-rrna-sequencing, ars, gut-microbiome, insoluble-fiber, ivermectin, np306, shime, short-chain-fatty-acids-scfas, soluble-fiber
Organization: Department of Agriculture
Data from: Expansion of Proteome-wide <i>Coxiella burnetii </i>Comparative T-cell Epitope Prediction to Include Small Ruminant Hosts

<p dir="ltr">T-cell epitopes represent sampled environmental- and self-peptides loaded into major histocompatibility complex (MHC) proteins. Bioinformatic tools have been produced to predict these interactions for many species, providing peptides of interest in vaccine development studies.</p><p dir="ltr">Prior work by the researchers (<a href="https://doi.org/10.1186/s12859-021-04181-w" rel="noreferrer" target="_blank">DOI: 10.1186/s12859-021-04181-w</a>) assessed the ability of <i>Coxiella burnetii </i>proteins to interact with MHC alleles in human, mouse, and cattle species, the data from which is available on the Open Science Framework repository with accession number RN6QA (<a href="https://osf.io/rn6qa/" rel="noreferrer" target="_blank">DOI: 10.17605/OSF.IO/RN6QA</a>).</p><p dir="ltr">Presently, bioinformatic programs <a href="https://services.healthtech.dtu.dk/services/NetBoLAIIpan-1.0/" rel="noreferrer" target="_blank">NetBoLAIIpan 1.0</a> and <a href="https://services.healthtech.dtu.dk/services/NetMHCpan-4.1/" target="_blank">NetMHCpan 4.1</a> were employed to predict T-cell epitopes within the <i>C. burnetii </i>proteome for the small ruminant species and to expand cattle predictions. The new datasets available herein provide the species, amino acid sequence, position within the protein, GenBank ID, allele name, and the predicted binding strength for each tested peptide.</p>

Tags: bioinformatics, coxiella-burnetii, reverse-vaccinology, small-ruminants, subunit-vaccine-targets, t-cell-epitopes-prediction
Organization: Department of Agriculture
Genes of viral origin in the Fopius arisanus genome

<p><em>Fopius arisanus</em> (Sonan) is a braconid wasp (subfamily Opiinae) and biological control agent of a broad range of tephritid fruit fly species, including the global pests Mediterranean fruit fly <em>Ceratitis capitata</em> and the Oriental fruit fly <em>Bactrocera dorsalis</em>. In an effort to create foundational genomic resources for this species, the complete genome and transcriptomes for several wasp life stages have been recently generated. Manual annotation of 55 viral genes and phylogenetic analysis revealed that <em>F. arisanus</em> has independently acquired a symbiotic virus related to alpha-nudiviruses. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: FARI_manual_annotations_1-19-2018_gburke.</p> <p>File Name: FARI_manual_annotations_1-19-2018_gburke.tar.gz</p><p>Resource Description: This set of data contains three fasta files (coding sequences, peptide sequences, and transcript sequences) from genes of viral origin annotated in the <em>F. arisanus</em> genome. A single gff3 file contains the annotations in tab delimited format.</p></li></ul><p></p>

Tags: ars, data-gov, np304
Organization: Department of Agriculture
U.S. National Insect Collection Database

<p>This subset of the U.S. National Insects Collection, which is primarly housed by the Smithsonian Institution's National Museum of Natural History, comprises the Coccomorpha (scale insects), Aphidomorpha (aphids), Alyrodomorpha (whiteflies), Psyllomorpha (psyllids), Thysanoptera (thrips),  and Acari (mites) collections.</p>
<p>Information about the Aphidomorpha (Aphididae, Adelgidae, and Phylloxeridae) samples is available through this database.</p>
<p>To search for one of these subgroups, use the "family" dropdown on one of the search subpages. You can search by Field or Keywords, and may also restrict your search to Genetic Samples, Primary Type Specimens, Species Inventory, Specimen Inventory, records with images, records with geo-referenced localities, or Illustrations. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Department of Entomology Collections.</p> <p>File Name: Web Page, url: <a href="http://collections.nmnh.si.edu/search/ento/">http://collections.nmnh.si.edu/search/ento/</a> </p><p>The online catalog for this collection</p></li></ul><p></p>

Tags: acari, alyrodomorpha, aphid, aphidomorpha, ars, coccomorpha, data-gov, exoskeletons, insects, mites, online-database, organisms, psyllids, psyllomorpha, scale-insects, thrips, thysanoptera, whitefly
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Climate Exposure Precipitation Winter Percent (Map Service)

The percent difference in Winter precipitation (in) between the reference time period of 1900-2014 and the current time period 2015-2019. Winter months include December, January, and February. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.

Tags: gtac, open-data, precipitation, tca, usfs
Organization: Department of Agriculture
Snowmelt Runoff Model for Windows (WinSRM)

<p>The Snowmelt-Runoff Model (WinSRM) is designed to simulate and forecast daily streamflow in mountain basins where snowmelt is a major runoff factor. The Snowmelt Runoff Model (SRM) is a simple degree-day model that requires remote sensing input in the form of basin or zonal snow cover extent. The model has been tested successfully on over 60 basins worldwide in the simulation and forecast modes. Model variables are derived from actual observations of temperature, precipitation, and snow covered area. Model parameters can either be derived from measurements or estimated by hydrological judgement taking into account the basin characteristics, physical laws, and theoretical or empirical relationships. To facilitate use of SRM, a microcomputer version of the program has been developed for IBM compatible personal computers. The program itself features user-oriented input and multiple self-help screens which allow the user to select the kind of data input employed and the output products desired. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Snowmelt Runoff Model for Windows (WinSRM).</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=7&modecode=80-42-05-10">https://www.ars.usda.gov/research/software/download/?softwareid=7&modecode=80-42-05-10</a> </p><p>download page</p></li></ul><p></p>

Tags: basins, climate, computer-software, glaciers, heat-sums, models, remote-sensing, satellites, snow, snowmelt, snowmelt-runoff-model, snowpack, stream-flow, temperature
Organization: Department of Agriculture
Soil Temperature and Moisture Model

<p>Purpose: The STM2 model predicts the soil temperature and moisture conditions based on very limited user inputs.  The input requirements are:</p>
<ol>
<li>A general soil characterization (soil texture and organic matter content)</li>
<li>Daily weather information limited to maximum and minimum air temperatures with daily precipitation.</li>
</ol>
<p>There is a help file that describes the program included in the file list below (STM2_description.doc).</p>
<p>Disclaimer: The USDA-ARS makes no warranties as to the merchantability or fitness of STM2 for any particular purpose, or any other warranties expressed or implied. Since some portions of STM2 have been validated with only limited data sets, it should not be used to make operational management decisions. The USDA-ARS is not liable for any damages resulting from the use or misuse of STM2, its output and its accompanying documentation.</p>
<p>STM2 was written in Java, and therefore can run on multiple platforms (e.g. Windows, Mac, Unix). </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Soil Temperature and Moisture Model.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=209&modecode=50-60-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=209&modecode=50-60-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, data-gov, np212
Organization: Department of Agriculture
Data from: Host range, biology, and thermal tolerance of <i>Lygomusotima stria</i>, a potential biological control agent of Old World climbing fern (<i>Lygodium microphyllum</i>) in the USA

<p dir="ltr">A potential biological control agent, <i>Lygomusotima stria </i>was collected in Thailand and Singapore and examined to determine if it was safe for release for <i>Lygodium microphyllum</i>. Old World climbing fern is one of the worst weeds of southern and central Florida. Old World climbing fern invades much of the southern peninsula of Florida where cost-effective, sustainable control methods are needed. Biological controls will assist land managers, reducing cost of control, and human exposure to pesticides. This agent has been recommended for field release by USDA APHIS.</p><p dir="ltr">Data in csv format included here is from a series of no-choice tests on neonate and third instars, oviposition, multigeneration, lower lethal temperature studies. Also included are native range collection information of <i>L. stria</i> and distribution data for the native <i>Lygodium palmatum</i>. A guide to the data files is included as 'Data files submitted to Ag Data Commons'. </p>

Tags: host-range-tests, lygodium, no-choice-test, weed-biological-control
Organization: Department of Agriculture
Plant Expression Database

<p>[NOTE: PLEXdb is no longer available online. Oct 2019.]</p>
<p>PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens. PLEXdb is a genotype to phenotype, hypothesis building information warehouse, leveraging highly parallel expression data with seamless portals to related genetic, physical, and pathway data.</p>
<p>PLEXdb (<a href="http://www.plexdb.org">http://www.plexdb.org</a>), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function and regulation of genes in economically important plants. A list of Gene Atlas experiments highlights data sets that give responses across different developmental stages, conditions and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs. The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation under diverse conditions or checking any gene’s suitability as a steady-state control.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer for Plant Expression Database, Iowa State University.</p> <p>File Name: Web Page, url: <a href="https://www.bcb.iastate.edu/plant-expression-database" target="_blank">https://www.bcb.iastate.edu/plant-expression-database</a> </p><p>[NOTE: PLEXdb is no longer available online. Oct 2019.]
Project description for the Plant Expression Database (PLEXdb) and integrated tools.</p></li></ul>

Tags: analysis-of-variance, arabidopsis, complementary-dna, data-collection, databases, developmental-stages, gene-expression, genes, genetic-databases, genotype, models, phenotype, plant-pathogens, rice, tissues
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Climate Exposure Temperature Summer (Map Service)

The difference in Summer temperature (F) between the reference time period of 1900-2014 and the current time period 2015-2019. Fall months include June, July, August. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.

Tags: gtac, open-data, tca, temperature, usfs
Organization: Department of Agriculture