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Found 46 result(s)
Project Data Sphere, LLC, operates a free digital library-laboratory where the research community can broadly share, integrate and analyze historical, de-identified, patient-level data from academic and industry cancer Phase II-III clinical trials. These patient-level datasets are available through the Project Data Sphere platform to researchers affiliated with life science companies, hospitals and institutions, as well as independent researchers, at no cost and without requiring a research proposal.
The NCI's Genomic Data Commons (GDC) provides the cancer research community with a unified data repository that enables data sharing across cancer genomic studies in support of precision medicine. The GDC obtains validated datasets from NCI programs in which the strategies for tissue collection couples quantity with high quality. Tools are provided to guide data submissions by researchers and institutions.
The Saccharomyces Genome Database (SGD) provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms.
MEASURE DHS is advancing global understanding of health and population trends in developing countries through nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, HIV, and nutrition. The database collects, analyzes, and disseminates data from more than 300 surveys in over 90 countries. MEASURE DHS distributes, at no cost, survey data files for legitimate academic research.
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
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>>>!!!<<< Data originally published in the JCB DataViewer has been moved BioStudies. Please note that while the majority of data were moved, some authors opted to remove their data completely. >>>!!!<<< Migrated data can be found at https://www.ebi.ac.uk/biostudies/JCB/studies. Screen data are available in the Image Data Resource repository. http://idr.openmicroscopy.org/webclient/?experimenter=-1 >>>!!!<<< The DataViewer was decommissioned in 2018 as the journal evolved to an all-encompassing archive policy towards original source data and as new data repositories that go beyond archiving data and allow investigators to make new connections between datasets, potentially driving discovery, emerged. JCB authors are encouraged to make available all datasets included in the manuscript from the date of online publication either in a publicly available database or as supplemental materials hosted on the journal website. We recommend that our authors store and share their data in appropriate publicly available databases based on data type and/or community standard. >>>!!!<<<
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
The world’s largest collection of TCR and BCR sequences. Easily incorporate millions of sequences worth of public data into your next papers and projects using immunoSEQ Analyzer. Construct your own projects, draw your own conclusions, and freely publish new discoveries.
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BCCM/ITM is a collection of well documented mycobacteria, characterized by phenotypic and/or genotypic tests. While having an emphasis on (drug-resistant) M. tuberculosis complex, BCCM/ITM comprises more than 90 mycobacterial species from human, animal and environmental origin from all continents.
Novartis provides the technical results and trial summaries for patients from Phase 1 through 4 interventional trials for innovative products within one year of trial completion. A trial summary for patients is a trial result written in easier to understand language than the technical results.
Content type(s)
Results from time-series analysis of Landsat images in characterizing global forest extent and change from 2000 through 2016.
THIN is a medical data collection scheme that collects anonymised patient data from its members through the healthcare software Vision. The UK Primary Care database contains longitudinal patient records for approximately 6% of the UK Population. The anonymised data collection, which goes back to 1994, is nationally representative of the UK population.
The OFA databases are core to the organization’s objective of establishing control programs to lower the incidence of inherited disease. Responsible breeders have an inherent responsibility to breed healthy dogs. The OFA databases serve all breeds of dogs and cats, and provide breeders a means to respond to the challenge of improving the genetic health of their breed through better breeding practices. The testing methodology and the criteria for evaluating the test results for each database were independently established by veterinary scientists from their respective specialty areas, and the standards used are generally accepted throughout the world.
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 ISRCTN registry is a primary clinical trial registry recognised by WHO and ICMJE that accepts all clinical research studies (whether proposed, ongoing or completed), providing content validation and curation and the unique identification number necessary for publication. All study records in the database are freely accessible and searchable. ISRCTN supports transparency in clinical research, helps reduce selective reporting of results and ensures an unbiased and complete evidence base. ISRCTN accepts all studies involving human subjects or populations with outcome measures assessing effects on human health and well-being, including studies in healthcare, social care, education, workplace safety and economic development.
DNASU is a central repository for plasmid clones and collections. Currently we store and distribute over 200,000 plasmids including 75,000 human and mouse plasmids, full genome collections, the protein expression plasmids from the Protein Structure Initiative as the PSI: Biology Material Repository (PSI : Biology-MR), and both small and large collections from individual researchers. We are also a founding member and distributor of the ORFeome Collaboration plasmid collection.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
The COVID-19 pandemic has affected every country in the world. It is well documented that those most susceptible to the worst outcomes of COVID-19 are the immunocompromised and those with underlying comorbidities. Therefore, patients requiring treatment for COVID-19 will also be on additional medication, posing a risk for drug-drug interactions (DDIs). In order to address this, the Liverpool Drug Interactions website team developed this freely available drug interactions resource to provide information on the likelihood of interactions between the experimental agents used for the treatment of COVID-19 and commonly prescribed co-medications.