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Found 33 result(s)
Museum explorers travel to ocean depths, the peaks of the Andes, Africa's Rift Valley, the rainforests of South America, and the deserts of Central Asia. Perhaps even to a field site or research institution in your own state, territory or country. In each area, researchers collect specimens: fossils, minerals, and rocks, plants and animals, tools and artworks. Collections care professionals have meticulously preserved, labeled, cataloged, and organized items of this kind for more than 150 years. Taken together, the NMNH collections form the largest, most comprehensive natural history collection in the world. By comparing items gathered in different eras and regions, scientists learn how our world has varied across time and space.
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
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PANGAEA - Data Publisher for Earth & Environmental Sciences has an almost 30-year history as an open-access library for archiving, publishing, and disseminating georeferenced data from the Earth, environmental, and biodiversity sciences. Originally evolving from a database for sediment cores, it is operated as a joint facility of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) and the Center for Marine Environmental Sciences (MARUM) at the University of Bremen. PANGAEA holds a mandate from the World Meteorological Organization (WMO) and is accredited as a World Radiation Monitoring Center (WRMC). It was further accredited as a World Data Center by the International Council for Science (ICS) in 2001 and has been certified with the Core Trust Seal since 2019. The successful cooperation between PANGAEA and the publishing industry along with the correspondent technical implementation enables the cross-referencing of scientific publications and datasets archived as supplements to these publications. PANGAEA is the recommended data repository of numerous international scientific journals.
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This data repository allows users to publish animal tracking datasets that have been uploaded to Movebank (https://www.movebank.org/ ). Published datasets have gone through a submission and review process, and are typically associated with a written study published in an academic journal. All animal tracking data in this repository are available to the public.
TriTrypDB is an integrated genomic and functional genomic database for pathogens of the family Trypanosomatidae, including organisms in both Leishmania and Trypanosoma genera. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.
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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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'Redape' is a digital repository that aims to preserve and disseminate research data produced by the Brazilian Agricultural Research Corporation - Embrapa. It allows the organization, management and publication of data in accordance with the FAIR principles.
CryptoDB is an integrated genomic and functional genomic database for the parasite Cryptosporidium and other related genera. CryptoDB integrates whole genome sequence and annotation along with experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining.
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DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
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The Swedish Infrastructure for Ecosystem Science (SITES) is a national infrastructure for terrestrial and limnological field research. SITES aims to promote high-quality research through long-term field measurements and field experiments, and by making data available. Quality-controlled monitoring data from SITES is freely available on the SITES Data Portal from all participating stations and thematic programs. New datasets are continuously being uploaded.
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The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education.
The South African Marine Information Management System (MIMS) is an Open Archival Information System (OAIS) repository that plays a multifaceted role in archiving, publishing, and preserving marine-related datasets. As an IODE-accredited Associate Data Unit (ADU), MIMS serves as a national node for the IODE of the IOC of UNESCO. It archives and publishes collections and subsets of marine-related datasets for the National Department of Forestry, Fisheries, and the Environment (DFFE) and its regional partners. As an IOC member organization, DFFE is committed to supporting the long-term preservation and archival of marine and coastal data for South Africa and its regional partners, promoting open access to data, and encouraging scientific collaboration. Tasked with the long-term preservation of South Africa's marine and coastal data, MIMS functions as an institutional data repository. It provides primary access to all data collected by the DFFE Oceans and Coastal Research Directorate and acts as a trusted broker of scientific marine data for a wide range of South African institutions. MIMS hosts the IODE AFROBIS Node, an OBIS Node that coordinates and collates data management activities within the sub-Saharan African region. As part of the OBIS Steering Group, MIMS represents sub-Saharan Africa on issues around biological (biodiversity) data standards. It also facilitates data and metadata publishing for the region through the GBIF and OBIS networks. Operating on the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles, MIMS aligns its practices to maximize ocean data exchange and use while respecting the conditions stipulated by the Data Provider. By integrating various functions and commitments, MIMS stands as a vital component in the marine and coastal data landscape, fostering collaboration, standardization, and accessibility in alignment with international standards and regional needs.