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AgBioData

AgBioData is a consortium of people working at agricultural biological databases, data archives and knowledgebases who strives to identify common issues in database development, curation, and management, with the goal of creating database products that are more Findable, Accessible, Interoperable, and Reusable (FAIR). Currently, there are over 150 people from 30 different databases and resources within the AgBioData consortium. We strive to promote authentic, detailed and accurate communication between all parties involved in scientific data.

For all agriculturally database personnel, we recommend joining the AgBioData consortium, attending the monthly conference call seminars, joining a working group, and working with your counterparts in other databases. A little time invested now in working together and applying common standards can save a lot of time later and prevent duplicated efforts in the development of tools and resources.

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AgBioData Datasets

38 datasets

The Animal Quantitative Trait Loci Database (Animal QTLdb)

    The Animal Quantitative Trait Loci (QTL) Database (Animal QTLdb) strives to collect all publicly available trait mapping data, i.e. QTL (phenotype/expression, eQTL), candidate gene and association data (GWAS), and copy number variations (CNV) mapped to livestock animal genomes, in order to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features such as annotated genes.

    Raw Sequences of 17 Aspergillus Genomes from Ethiopia

      Raw genome sequencing data of 17 isolates of Aspergillus flavus and Aspergillus parasiticus collected from peanuts from Ethiopia. These isolates were selected as representative of the genetic diversity of Aspergillus section Flavi found colonizing peanut seeds in four peanut-farming districts of Ethiopia, these are Darolabu, Gursum, Fedis, and Babile.

      CottonGen: Cotton Database Resources

        CottonGen (https://www.cottongen.org) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data to enable basic, translational and applied research in cotton. Built using the open-source Tripal database infrastructure, CottonGen supersedes CottonDB and the Cotton Marker Database, which includes sequences, genetic and physical maps, genotypic and phenotypic markers and polymorphisms, quantitative trait loci (QTLs), pathogens, germplasm collections and trait evaluations, pedigrees, and relevant bibliographic citations, with enhanced tools for easier data sharing, mining, visualization, and data retrieval of cotton research data.

        Data from: Niche partitioning and coexistence of parasitoids of the same feeding guild introduced for biological control of an invasive forest pest

          The data set is collected to evaluate if two parasitoids (Spathius galinae and Tetrastichus planipennisi), introduced for biocontrol of the invasive emerald ash borer (EAB), Agrilus planipennis, into North America have established niche-partitioning, co-existing populations following their sequential or simultaneous field releases to 12 hard-wood forests located in Midwest and Northeast regions of the United States.

          TreeGenes

            The TreeGenes database provides custom informatics tools to manage the flood of information resulting from high-throughput genomics projects in forest trees from sample collection to downstream analysis. This resource is enhanced with systems that are well connected with federated databases, automated data flows, machine learning analysis, standardized annotations and quality control processes. The database itself contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools.

            i5K Workspace@NAL

              The i5k Workspace @ NAL is a platform for communities around ‘orphaned’ arthropod genome projects to access, visualize, curate and disseminate their data.

              Legume Information System

                The Legume Information System ([legumeinfo.org](https://legumeinfo.org "Legume Information System")) is the USDA-ARS genetics and genomics database for legume crops and relatives. Researchers can also submit their data directly. LIS houses data for more than a dozen species such as common bean and chickpea, peanut, and soybean, with genome sequences, genes and predicted functions, families of related genes, views of evolutionary relationships between genomic regions, genetic maps, markers, and links to germplasm resources.

                The GRIN-Global Project

                  GRIN-Global is an ongoing international collaborative project to develop shared and open-source applications that help manage plant germplasm collections.