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Found 10 result(s)
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INRAE is the world’s first organisation specialized on agricultural, food and environmental sciences. Data INRAE is offered by INRAE as part of its mission to open the results of its research. Data INRAE will share research data in relation with food, nutrition, agriculture and environment. It includes experimental, simulation and observation data, omic data, survey and text data. Only data produced by or in collaboration with INRAE will be hosted in the repository, but anyone can access the metadata and the open data.
Using a combination of remote sensing data and ground observations as inputs, CHC scientists have developed rainfall estimation techniques and other resources to support drought monitoring and predict crop performance in parts of the world vulnerable to crop failure. Policymakers within governments and non-governmental organizations rely on CHC decision-support products to make critical resource allocation decisions. The CHC's scientific focus is "geospatial hydroclimatology," with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food-security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS NET countries (https://fews.net/). The CHC develops better techniques, algorithms, and modeling applications in order to use remote sensing and other geospatial data for hazards early warning.
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The Yeast Metabolome Database (YMDB) is a manually curated database of small molecule metabolites found in or produced by Saccharomyces cerevisiae (also known as Baker’s yeast and Brewer’s yeast). This database covers metabolites described in textbooks, scientific journals, metabolic reconstructions and other electronic databases.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> The Plant Organelles Database Version 3 (PODB3) is a specialized database project to promote a comprehensive understanding of organelle dynamics, including organelle function, biogenesis, differentiation, movement, and interactions with other organelles. This database consists of 6 individual parts, 'The Electron Micrograph Database', 'The Perceptive Organelles Database', 'The Organelles Movie Database', 'The Organellome Database', 'The Functional Analysis Database', and 'External Links to other databases and Web pages'. All the data and protocols in these databases are populated by direct submission of experimentally determined data from plant researchers.
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GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, association genetics, markers, polymorphisms, germplasms, phenotypes and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Research Institute for Agriculture, Food and Environment. It is regularly improved and released several times per year. GnpIS is accessible through a web portal and allows to browse different types of data either independently through dedicated interfaces or simultaneously using a quick search ('google like search') or advanced search (Biomart, Galaxy, Intermine) tools.
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The IPK stores a large volume of research results and information in various databases. The Institute of Plant Genetics and Crop Plant Research IPK Gatersleben, is a nonprofit research institution for crop genetics and molecular biology, and is part of the Leibniz Association. The mission of the IPK Gatersleben is to conduct basic and applied research in the area of plant genetics and crop plant research. The results of this work are not only of significant benefit to plant breeders and the agricultural industry, but also to the food, feed, and chemical industry. An additional research area, the use of renewable raw materials, is increasingly gaining in importance.
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.