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Found 24 result(s)
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
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Open At LaTrobe (OPAL) is La Trobe University’s official repository for Open Access materials generated by academic and professional staff and HDR students. These include publications and other research outputs, theses, open data, and educational resources. OPAL enables the storage, sharing, and selective publication of files and the assignment of a persistent DOI. Users maintain control over who can see their private files and all uploads are stored in La Trobe University approved storage. Access is via La Trobe University login credentials. La Trobe produces a wide range of useful datasets including supplementary data associated with publications and stand-alone datasets and collections.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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.
The Centre for Environmental Data Analysis (CEDA) serves the environmental science community through managing data centres, data analysis environments, and participation in a host of relevant research projects. We aim to support environmental science, further environmental data archival practices, and develop and deploy new technologies to enhance access to data. Additionally we provide services to aid large scale data analysis. The CEDA Archive operates the atmospheric and earth observation data centre functions on behalf of NERC for the UK atmospheric science and earth observation communities. It covers climate, composition, observations and NWP data as well as various earth observation datasets, including airborne and satellite data and imagery. Prior to November 2016 these functions were operted by CEDA under the titles of the British Atmospheric Data Centre (BADC) and the NERC Earth Observation Data Centre (NEODC). CEDA also operates the UK Solar System Data Centre (UKSSDC), which curates and provides access to archives of data from the upper atmosphere, ionosphere and Earth's solar environment.
<<<!!!<<< This repository is no longer available>>>!!!>>>. Although the web pages are no longer available, you will still be able to download the final UniGene builds as static content from the FTP site https://ftp.ncbi.nlm.nih.gov/repository/UniGene/. You will also be able to match UniGene cluster numbers to Gene records by searching Gene with UniGene cluster numbers. For best results, restrict to the “UniGene Cluster Number” field rather than all fields in Gene. For example, a search with Mm.2108[UniGene Cluster Number] finds the mouse transthyretin Gene record (Ttr). You can use the advanced search page https://www.ncbi.nlm.nih.gov/gene/advanced to help construct these searches. Keep in mind that the Gene record contains selected Reference Sequences and GenBank mRNA sequences rather than the larger set of expressed sequences in the UniGene cluster.
TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.
<<<!!!<<< As of 2023, support to maintain the www.modencode.org and intermine.modencode.org sites have been retired following the end of funding. To access data from the modENCODE project, or for questions regarding the data they make available, please visit these databases: Fly data: FlyBase: ModENCODE data at FlyBase: https://wiki.flybase.org/wiki/FlyBase:ModENCODE_data_at_FlyBase FlyBase: https://www.re3data.org/repository/r3d100010591 Worm data: WormBase https://www.re3data.org/repository/r3d100010424 Data, including modENCODE and modERN project data, is also available at the ENCODE Portal: https://www.re3data.org/repository/r3d100013051 (search metadata and view datasets for Drosophila and Caenorhabditis https://www.encodeproject.org/matrix/?type=Experiment&control_type!=*&status=released&replicates.library.biosample.donor.organism.scientific_name=Drosophila+melanogaster&replicates.library.biosample.donor.organism.scientific_name=Caenorhabditis+elegans&replicates.library.biosample.donor.organism.scientific_name=Drosophila+pseudoobscura&replicates.library.biosample.donor.organism.scientific_name=Drosophila+mojavensis). >>>!!!>>>
ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
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HYdrological cycle in the Mediterranean EXperiemnt. Considering the science and societal issues motivating HyMeX, the programme aims to : improve our understanding of the water cycle, with emphasis on extreme events, by monitoring and modelling the Mediterranean atmosphere-land-ocean coupled system, its variability from the event to the seasonal and interannual scales, and its characteristics over one decade (2010-2020) in the context of global change, assess the social and economic vulnerability to extreme events and adaptation capacity.The multidisciplinary research and the database developed within HyMeX should contribute to: improve observational and modelling systems, especially for coupled systems, better predict extreme events, simulate the long-term water-cycle more accurately, provide guidelines for adaptation measures, especially in the context of global change.
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The Coriolis Data Centre handles operational oceanography measurements made in situ, complementing the measurement of the ocean surface made using instruments aboard satellites. This work is realised through the establishment of permanent networks with data collected by ships or autonomous systems that are either fixed or drifting. This data can be used to construct a snapshot of water mass structure and current intensity.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials
MERMex is focused on the biogeochemical changes that will take place in the Mediterranean Sea due to natural changes as well as the socio-economic impacts, and how they will affect marine ecosystems and biodiversity.
UNAVCO promotes research by providing access to data that our community of geodetic scientists uses for quantifying the motions of rock, ice and water that are monitored by a variety of sensor types at or near the Earth's surface. After processing, these data enable millimeter-scale surface motion detection and monitoring at discrete points, and high-resolution strain imagery over areas of tens of square meters to hundreds of square kilometers. The data types include GPS/GNSS, imaging data such as from SAR and TLS, strain and seismic borehole data, and meteorological data. Most of these can be accessed via web services. In addition, GPS/GNSS datasets, TLS datasets, and InSAR products are assigned digital object identifiers.
BioMagResBank (BMRB) is the publicly-accessible depository for NMR results from peptides, proteins, and nucleic acids recognized by the International Society of Magnetic Resonance and by the IUPAC-IUBMB-IUPAB Inter-Union Task Group on the Standardization of Data Bases of Protein and Nucleic Acid Structures Determined by NMR Spectroscopy. In addition, BMRB provides reference information and maintains a collection of NMR pulse sequences and computer software for biomolecular NMR
EOL’s platforms and instruments collect large and often unique data sets that must be validated, archived and made available to the research community. The goal of EOL data services is to advance science through delivering high-quality project data and metadata in ways that are as transparent, secure, and easily accessible as possible - today and into the future. By adhering to accepted standards in data formats and data services, EOL provides infrastructure to facilitate discovery and direct access to data and software from state-of-the-art commercial and locally-developed applications. EOL’s data services are committed to the highest standard of data stewardship from collection to validation to archival.
SRUC is currently on a transformational journey as we move towards becoming a unique, market-led and mission diverse 21st Century rural university, driving the future needs of a dynamic, innovative and competitive rural sector in Scotland, and working with our collaborators and partners worldwide to solve the biggest global agrifood challenges. Our researchers already carry out strategic and applied research on global and local food security issues, and actively support the translation of research results into practice. Our research ethos is strongly collaborative, and we have a long history of industrial, NGO and academic partnerships locally and internationally. As well as having longstanding disciplinary strengths in several key areas, we actively promote interdisciplinary research, especially linking natural and social sciences. We have a particular interest in research that helps inform policy, with Scottish and UK Government rural affairs and environment departments and the EU as key research clients.
British Antarctic Survey (BAS) has, for over 60 years, undertaken the majority of Britain's scientific research on and around the Antarctic continent. Atmospheric, biosphere, cryosphere, geosphere, hydrosphere, and Sun-Earth interactions metadata and data are available. Geographic information and collections are highlighted as well. Information and mapping services include a Discovery Metadata System, Data Access System, the Antarctic Digital Database (ADD), Geophysics Data Portal (BAS-GDP), ICEMAR, a fossil database, and the Antarctic Plant Database.
MetaboLights is a database for Metabolomics experiments and derived information. The database is cross-species, cross-technique and covers metabolite structures and their reference spectra as well as their biological roles, locations and concentrations, and experimental data from metabolic experiments.