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Found 1020 result(s)
>>>!!!<<< Ecological Archives through the end of 2015 will be hosted on FigShare once the transition to publishing with Wiley is completed. Thereafter, supplemental material may be hosted on Wiley Online, and/or data deposited with FigShare, Dryad, and other repositories. >>>!!!<<< Ecological Archives publishes materials that are supplemental to articles that appear in the ESA journals (Ecology, Ecological Applications, Ecological Monographs, Ecosphere, Ecosystem Health and Sustainability and Bulletin of the Ecological Society of America), as well as peer-reviewed data papers with abstracts published in the printed journals. Three kinds of publications appear in Ecological Archives: appendices, supplements, and data papers.
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The objective of this project is to generate the most comprehensive description of human chromosome 7 to facilitate biological discovery, disease gene research and medical genetic applications. In our vision, the DNA sequence of chromosome 7 should be made available in a user-friendly manner having every biological and medically relevant feature annotated along its length. We have established this website and database as one step towards this goal. In addition to being a primary data source we foresee this site serving as a "weighing station" for testing community ideas and information to produce highly curated data to be submitted to other databases such as NCBI, Ensembl, and UCSC. Therefore, any useful data submitted to us will be curated and shown in this database.
Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship (PROFILES)’ is a registry for the study of the physical and psychosocial impact of cancer and its treatment from a dynamic, growing population-based cohort of both short and long-term cancer survivors. Researchers from the Netherlands Comprehensive Cancer Centre and Tilburg University in Tilburg, The Netherlands, work together with medical specialists from national hospitals in order to setup different PROFILES studies, collect the necessary data, and present the results in scientific journals and (inter)national conferences.
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FlyCircuit is a public database for online archiving, cell type inventory, browsing, searching, analysis and 3D visualization of individual neurons in the Drosophila brain. The FlyCircuit Database currently contains about 30,000 high resolution 3D brain neural images of the drosophila fruit fly brain that are combined into a neural circuitry network that researchers can use as a blueprint to further explore how the brain of a fruit fly processes external sensory signals (i.e. how vision, hearing, and smell are transmitted to the central nerve system).
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>>>!!!<<< OMICtools is no longer online >>>!!!<<< We founded OMICtools in 2012 with the vision to drive progress in life science. We wanted to empower life science practitioners all over the world to achieve breakthroughs by getting data to talk. While we made tremendous progress over the past three years, developing a bioinformatics database of software and dynamic protocols, attracting more than 1.5M visitors a year, we lacked the financial support we needed to continue. We certainly gave it our all. We'd like to thank everyone who believed in us and supported us on this journey: all our users, our community, our friends, families and employees (who we consider as our extended family!). omicX will probably shut down its operations within the next few weeks. The team and I remain firmly committed to our vision, particularly at this very difficult time. It is now, more than ever before, that researchers need access to a resource that pools collective scientific intelligence. We have accumulated an awful lot of experience which we are keen to share. If your institution would be interested in taking over our website and database, to provide researchers with continued access to the platform, or you simply want to stay in touch with the omicX team, contact us at contact@omictools.com or at carine.toutain@fhbx.eu.
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APID Interactomes is a database that provides a comprehensive collection of protein interactomes for more than 400 organisms based in the integration of known experimentally validated protein-protein physical interactions (PPIs). Construction of the interactomes is done with a methodological approach to report quality levels and coverage over the proteomes for each organism included. In this way, APID provides interactomes from specific organisms that in 25 cases have more than 500 proteins. As a whole APID includes a comprehensive compendium of 90,379 distinct proteins and 678,441 singular interactions. The analytical and integrative effort done in APID unifies PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. In this way, 8,388 structures have been analyzed to find specific protein-protein interactions reported with details of their molecular interfaces. APID also includes a new data visualization web-tool that allows the construction of sub-interactomes using query lists of proteins of interest and the visual exploration of the corresponding networks, including an interactive selection of the properties of the interactions (i.e. the reliability of the "edges" in the network) and an interactive mapping of the functional environment of the proteins (i.e. the functional annotations of the "nodes" in the network).
The Comparative RNA Web (CRW) Site disseminates information about RNA structure and evolution that has been determined using comparative sequence analysis. We present both raw (sequences, structure models, metadata) and processed (analyses, evolution, accuracy) data, organized into four main sections.
The Korea Polar Data Center (KPDC) is an organization dedicated for managing different types of data acquired during scientific research that South Korea carries out in Antarctic and Arctic regions. South Korea, as an Antarctic Treaty Consultative Party (ATCP) and an accredited member of the Scientific Committee on Antarctic Research (SCAR) established the Center in 2003 as part of its effort to joint international Antarctic research.
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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.
NetSlim is a resource of high-confidence signaling pathway maps derived from NetPath pathway reactions. 40-60% of the molecules and their reactions in NetPath pathways are available in NetSlim.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
The USDA Agricultural Marketing Service (AMS) Cotton Program maintains a National Database (NDB) in Memphis, Tennessee for owner access to cotton classification data. The NDB is computerized telecommunications system which allows owners or authorized agents of owners to retrieve classing data from the current crop and/or the previous four crops. The NDB stores classing information from all 10 regional classing offices.
ALSoD is a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.
The Deep Carbon Observatory (DCO) is a global community of multi-disciplinary scientists unlocking the inner secrets of Earth through investigations into life, energy, and the fundamentally unique chemistry of carbon. Deep Carbon Observatory Digital Object Registry (“DCO-VIVO”) is a centrally-managed digital object identification, object registration and metadata management service for the DCO. Digital object registration includes DCO-ID generation based on the global Handle System infrastructure and metadata collection using VIVO. Users will be able to deposit their data into the DCO Data Repository and have that data discoverable and accessible by others.
This is CSDB version 1 merged from Bacterial (BCSDB) and Plant&Fungal (PFCSDB) databases. This database aims at provision of structural, bibliographic, taxonomic, NMR spectroscopic and other information on glycan and glycoconjugate structures of prokaryotic, plant and fungal origin. It has been merged from the Bacterial and Plant&Fungal Carbohydrate Structure Databases (BCSDB+PFCSDB). The key points of this service are: High coverage. The coverage for bacteria (up to 2016) and archaea (up to 2016) is above 80%. Similar coverage for plants and fungi is expected in the future. The database is close to complete up to 1998 for plants, and up to 2006 for fungi. Data quality. High data quality is achieved by manual curation using original publications which is assisted by multiple automatic procedures for error control. Errors present in publications are reported and corrected, when possible. Data from other databases are verified on import. Detailed annotations. Structural data are supplied with extended bibliography, assigned NMR spectra, taxon identification including strains and serogroups, and other information if available in the original publication. Services. CSDB serves as a platform for a number of computational services tuned for glycobiology, such as NMR simulation, automated structure elucidation, taxon clustering, 3D molecular modeling, statistical processing of data etc. Integration. CSDB is cross-linked to other glycoinformatics projects and NCBI databases. The data are exportable in various formats, including most widespread encoding schemes and records using GlycoRDF ontology. Free web access. Users can access the database for free via its web interface (see Help). The main source of data is retrospective literature analysis. About 20% of data were imported from CCSD (Carbbank, University of Georgia, Athens; structures published before 1996) with subsequent manual curation and approval. The current coverage is displayed in red on the top of the left menu. The time lag between the publication of new data and their deposition into CSDB is ca. 1 year. In the scope of bacterial carbohydrates, CSDB covers nearly all structures of this origin published up to 2016. Prokaryotic, plant and fungal means that a glycan was found in the organism(s) belonging to these taxonomic domains or was obtained by modification of those found in them. Carbohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds in which at least one residue is a sugar or its derivative.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
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The ZFMK Biodiversity Data Center is aimed at hosting, archiving, publishing and distributing data from biodiversity research and zoological collections. The Biodiversity Data Center handles and curates data on: - The specimens of the institutes collection, including provenance, distribution, habitat, and taxonomic data. - Observations, recordings and measurements from field research, monitoring and ecological inventories. - Morphological measurements, descriptions on specimens, as well as - Genetic barcode libraries, and - Genetic and molecular research data associated with specimens or environmental samples. For this purpose, suitable software and hardware systems are operated and the required infrastructure is further developed. Core components of the software architecture are: The DiversityWorkbench suite for managing all collection-related information. The Digital Asset Management system easyDB for multimedia assets. The description database Morph·D·Base for morphological data sets and character matrices.
BindingDB is a public, web-accessible knowledgebase of measured binding affinities, focusing chiefly on the interactions of proteins considered to be candidate drug-targets with ligands that are small, drug-like molecules. BindingDB supports medicinal chemistry and drug discovery via literature awareness and development of structure-activity relations (SAR and QSAR); validation of computational chemistry and molecular modeling approaches such as docking, scoring and free energy methods; chemical biology and chemical genomics; and basic studies of the physical chemistry of molecular recognition. BindingDB also includes a small collection of host-guest binding data of interest to chemists studying supramolecular systems. The data collection derives from a variety of measurement techniques, including enzyme inhibition and kinetics, isothermal titration calorimetry, NMR, and radioligand and competition assays. BindingDB includes data extracted from the literature and from US Patents by the BindingDB project, selected PubChem confirmatory BioAssays, and ChEMBL entries for which a well defined protein target ("TARGET_TYPE='PROTEIN'") is provided.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.
The Complex Portal is a manually curated, encyclopaedic resource of macromolecular complexes from a number of key model organisms, entered into the IntAct molecular interaction database (https://www.ebi.ac.uk/intact/). Data includes protein-only complexes as well as protein-small molecule and protein-nucleic acid complexes. All complexes are derived from physical molecular interaction evidences extracted from the literature and cross-referenced in the entry, or by curator inference from information on homologs in closely related species or by inference from scientific background. All complexes are tagged with Evidence and Conclusion Ontology codes to indicate the type of evidence available for each entry.