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Found 202 result(s)
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<<<!!!<<< Genome data generated by BC Genome Sciences Centre is no longer available through this site as it is regularly deposited into controlled data repositories such as the European Genome Phenome Archive (EGA); ICGC (International Cancer Genome Consortium) and the Genome Data Commons (GDC) >>>!!!>>> Mapping, copy number analysis, sequence and gene expression data generated by the High Resolution Analysis of Follicular Lymphoma Genomes project. The data will be available for 24 patients with follicular lymphoma. All data will be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.The data from this project will be submitted to public genomic data sources. These sources will be listed on this web site as the data becomes available in these external data sources.
The European Genome-phenome Archive (EGA) is designed to be a repository for all types of sequence and genotype experiments, including case-control, population, and family studies. We will include SNP and CNV genotypes from array based methods and genotyping done with re-sequencing methods. The EGA will serve as a permanent archive that will archive several levels of data including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters. We are developing data mining and access tools for the database. For controlled access data, the EGA will provide the necessary security required to control access, and maintain patient confidentiality, while providing access to those researchers and clinicians authorised to view the data. In all cases, data access decisions will be made by the appropriate data access-granting organisation (DAO) and not by the EGA. The DAO will normally be the same organisation that approved and monitored the initial study protocol or a designate of this approving organisation. The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
The Coronavirus Antiviral Research Database is designed to expedite the development of SARS-CoV-2 antiviral therapy. It will benefit global coronavirus drug development efforts by (1) promoting uniform reporting of experimental results to facilitate comparisons between different candidate antiviral compounds; (2) identifying gaps in coronavirus antiviral drug development research; (3) helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development; (4) providing an objective, evidenced-based, source of information for the public; and (5) creating a hub for the exchange of ideas among coronavirus researchers whose feedback is sought and welcomed. By comprehensively reviewing all published laboratory, animal model, and clinical data on potential coronavirus therapies, the Database makes it unlikely that promising treatment approaches will be overlooked. In addition, by making it possible to compare the underlying data associated with competing treatment strategies, stakeholders will be better positioned to prioritize the most promising anti-coronavirus compounds for further development.
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
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Portal Zarządzania Wiedzą UJ CM is a knowledge and research potential management platform of medical information. Easy data localization will be possible thanks to DOI and URL addresses given by administrators of the Knowledge Management Platform JU MC. The data will be stored in 2 copies for 10 years.
The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. The NDA provides infrastructure for sharing research data, tools, methods, and analyses enabling collaborative science and discovery. De-identified human subjects data, harmonized to a common standard, are available to qualified researchers. Summary data is available to all. The primary point of entry to the NDA is currently through the National Database for Autism Research (NDAR) website, which serves the autism research community. All NDA repositories can be accessed through this website for data contribution and querying with other scientific communities, allowing for aggregation and secondary analysis of data.
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The sources of the data sets include data sets donated by researchers, surveys carried out by SRDA, as well as by government department and other academic organizations. Prior to the release of data sets, the confidentiality and sensitivity of every survey data set are evaluated. Standard data management and cleaning procedures are applied to ensure data accuracy and completeness. In addition, metadata and relevant supplement files are also edited and attached.
The NCBI Taxonomy database is a curated set of names and classifications for all of the organisms that are represented in GenBank. The EMBL and DDBJ databases, as well as GenBank, now use the NCBI Taxonomy as the standard classification for nucleotide sequences. Taxonomy Contains the names and phylogenetic lineages of more than 160,000 organisms that have molecular data in the NCBI databases. New taxa are added to the Taxonomy database as data are deposited for them. When new sequences are submitted to GenBank, the submission is checked for new organism names, which are then classified and added to the Taxonomy database.
BBMRI-ERIC is a European research infrastructure for biobanking. We bring together all the main players from the biobanking field – researchers, biobankers, industry, and patients – to boost biomedical research. To that end, we offer quality management services, support with ethical, legal and societal issues, and a number of online tools and software solutions. Ultimately, our goal is to make new treatments possible. The Directory is a tool to share aggregate information about the biobanks that are willing external collaboration. It is based on the MIABIS 2.0 standard, which describes the samples and data in the biobanks at an aggregated level.
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KRISHI Portal is an initiative of Indian Council of Agricultural Research (ICAR) to bring its knowledge resources to all stakeholders at one place. The portal is being developed as a centralized data repository system of ICAR consisting of Technology, Data generated through Experiments/ Surveys/ Observational studies, Geo-spatial data, Publications, Learning Resources etc. For implementation of research data management electronically in ICAR Institutes and digitization of agricultural research, KRISHI (Knowledge based Resources Information Systems Hub for Innovations in Agriculture) Portal has been developed as ICAR Research Data Repository for knowledge management. Data Inventory Repository aims at creating Meta Data Inventory through information related to data availability at Institute level. The portal consists of six repositories viz. technology, publication, experimental data, observational data survey data and geo-portal. The portal can be accessed at http://krishi.icar.gov.in. During the period of 2016-17, input data on latitude and longitude of all KVKs under this Zone was submitted to the concerned authority to put them in geo-portal. One brainstorming session was organized at this institute for all scientists on its use and uploading information in portal. As per guidelines of the council, various kinds of publications pertaining to this institute were also uploaded in this portal.
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A data repository for the storage and sharing of Adaptive Immune Receptor Repertoire data. Primary public repository for the iReceptor Platform and Scientific Gateway. Further URL for the repository: http://www.ireceptor.org
The Health Data Research Innovation Gateway (the ‘Gateway’) provides a common entry point to discover and enquire about access to UK health datasets for research and innovation. It provides detailed information about the datasets, which are held by members of the UK Health Data Research Alliance, such as a description, size of the population, and the legal basis for access. The Gateway includes the ability to search for research projects, publications and health data tools, such as those related to COVID-19. New interactive features provide a community forum for researchers to collaborate and connect and the ability to add research projects. The Innovation Gateway does not hold or store any datasets or patient or health data but rather acts as a portal to allow discovery of datasets and to request access to them for health research. A dataset is a collection of related individual pieces of data but in the case of health data, identifiable information (e.g. name or NHS number) is removed and data is de-identified where possible. When you access the Gateway you will not be able to view or extract the data itself. Instead, you will be able to see information that describes what the different datasets are (e.g. where the dataset has come from, a description of the dataset, the time period and the geographical areas the dataset covers).
EBRAINS offers one of the most comprehensive platforms for sharing brain research data ranging in type as well as spatial and temporal scale. We provide the guidance and tools needed to overcome the hurdles associated with sharing data. The EBRAINS data curation service ensures that your dataset will be shared with maximum impact, visibility, reusability, and longevity, https://ebrains.eu/services/data-knowledge/share-data. Find data - the user interface of the EBRAINS Knowledge Graph - allows you to easily find data of interest. EBRAINS hosts a wide range of data types and models from different species. All data are well described and can be accessed immediately for further analysis.
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The National Microbial Data Center (NMDC) is jointly constructed by the Institute of Microbiology of the Chinese Academy of Sciences (IMS), the Institute of Oceanography of the Chinese Academy of Sciences, the Institute of Infectious Diseases of the Chinese Center for Disease Control and Prevention, the Institute of Plant Physiology and Ecology of the Chinese Academy of Sciences, and the Computer Network Information Centre of the Chinese Academy of Sciences. The General Office of the Chinese Academy of Sciences is the parent department. The data resources covering the whole life cycle of microbiological research, including microbiological resources, microbiological and cross-technological methods, research processes and engineering, microbiomics, microbiological technologies, as well as microbiological literature, patents, experts and results. The Centre focuses on promoting the convergence and integration of scientific and technological resources in the field of microbiology to the national platform, strengthening the development, application and analysis of microbiological resources, enhancing the effective use of microbiological resources and the ability to support scientific and technological innovation, and providing high-quality scientific and technological resource sharing services for scientific research, technological progress and social development.
With the Program EnviDat we develop a unified and managed access portal for WSL's rich reservoir of environmental monitoring and research data. EnviDat is designed as a portal to publish, connect and search across existing data but is not intended to become a large data centre hosting original data. While sharing of data is centrally facilitated, data management remains decentralised and the know-how and responsibility to curate research data remains with the original data providers.
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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
<<<!!!<<< 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.
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The CyberCell database (CCDB) is a comprehensive collection of detailed enzymatic, biological, chemical, genetic, and molecular biological data about E. coli (strain K12, MG1655). It is intended to provide sufficient information and querying capacity for biologists and computer scientists to use computers or detailed mathematical models to simulate all or part of a bacterial cell at a nanoscopic (10-9 m), mesoscopic (10-8 m).The CyberCell database CCDB actually consists of 4 browsable databases: 1) the main CyberCell database (CCDB - containing gene and protein information), 2) the 3D structure database (CC3D – containing information for structural proteomics), 3) the RNA database (CCRD – containing tRNA and rRNA information), and 4) the metabolite database (CCMD – containing metabolite information). Each of these databases is accessible through hyperlinked buttons located at the top of the CCDB homepage. All CCDB sub-databases are fully web enabled, permitting a wide variety of interactive browsing, search and display operations. and microscopic (10-6 m) level.
<<<!!!<<< This repository is no longer available. >>>!!!>>> The sequencing of several bird genomes and the anticipated sequencing of many more provided the impetus to develop a model organism database devoted to the taxonomic class: Aves. Birds provide model organisms important to the study of neurobiology, immunology, genetics, development, oncology, virology, cardiovascular biology, evolution and a variety of other life sciences. Many bird species are also important to agriculture, providing an enormous worldwide food source worldwide. Genomic approaches are proving invaluable to studying traits that affect meat yield, disease resistance, behavior, and bone development along with many other factors affecting productivity. In this context, BirdBase will serve both biomedical and agricultural researchers.
The Neuroscience Information Framework is a dynamic index of data, materials, and tools. Please note, we do not accept direct data deposits, but if you wish to make your data repository or database available through our search, please contact us. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.
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The portal "Wissenschaftliche Sammlungen" is a project of the Coordination Office for Academic University Collections in Germany in cooperation with the Academic University and University Collections. Together we create a platform that makes information on scientific collections, activities and actors as well as metadata and digitised objects visible, searchable and scientifically usable via a web portal. The data will be freely and openly accessible via technical interfaces in standard formats and fed into national reference systems such as the German Digital Library.