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Found 16 result(s)
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
Country
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
XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization. NOTICE: Central XNAT will be decommissioned on October 15, 2023. New project creation is no longer permitted.
Patients-derived tumor xenograft (PDX) mouse models are an important oncology research platform to study tumor evolution, drug response and personalised medicine approaches. We have expanded to organoids and cell lines and are now called CancerModels.Org
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The repository is no longer available. <<<!!!<<< Visit IRIS at EPA: https://www.epa.gov/iris >>>!!!>>>
arrayMap is a repository of cancer genome profiling data. Original) from primary repositories (e.g. NCBI GEO, EBI ArrayExpress, TCGA) is re-processed and annotated for metadata. Unique visualization of the processed data allows critical evaluation of data quality and genome information. Structured metadata provides easy access to summary statistics, with a focus on copy number aberrations in cancer entities.
Country
More than a quarter of a million people — one in 10 NSW men and women aged over 45 — have been recruited to our 45 and Up Study, the largest ongoing study of healthy ageing in the Southern Hemisphere. The baseline information collected from all of our participants is available in the Study’s Data Book. This information, which researchers use as the basis for their analyses, contains information on key variables such as height, weight, smoking status, family history of disease and levels of physical activity. By following such a large group of people over the long term, we are developing a world-class research resource that can be used to boost our understanding of how Australians are ageing. This will answer important health and quality-of-life questions and help manage and prevent illness through improved knowledge of conditions such as cancer, heart disease, depression, obesity and diabetes.
<<<!!!<<<The repository is no longer available <<<!!!<<< TOXNET has moved. Most content will continue to be collected and reviewed; selected information is accessible through PubChem, PubMed, and Bookshelf. If you have questions, please contact NLM Customer Support at https://support.nlm.nih.gov/ >>>!!!>>>
The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary cancer by providing electronic access to: Information on endogenous spontaneous and induced tumors in mice, including tumor frequency & latency data, Information on genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice) in which tumors arise, Information on genetic factors associated with tumor susceptibility in mice and somatic genetic-mutations observed in the tumors, Tumor pathology reports and images, References, supporting MTB data and Links to other online resources for cancer.
The repository is no longer available. <<<!!!<<< CCRIS information is migrated to PubChem (https://www.ncbi.nlm.nih.gov/pcsubstance?term=%22Chemical%20Carcinogenesis%20Research%20Information%20System%20(CCRIS)%22%5BSourceName%5D%20AND%20hasnohold%5Bfilt%5D) Help for CCRIS Users in PubChem: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.html or PDF: https://www.nlm.nih.gov/toxnet/Accessing_CCRIS_Content_from_PubChem.pdf. >>>!!!>>>
The Cancer Immunome Database (TCIA) provides results of comprehensive immunogenomic analyses of next generation sequencing data (NGS) data for 20 solid cancers from The Cancer Genome Atlas (TCGA) and other datasource. The Cancer Immunome Atlas (TCIA) was developed and is maintained at the Division of Bioinformatics (ICBI). The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). Moreover it provides survival analyses for different types immunological parameters. TCIA will be constantly updated with new data and results.
TCIA is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. The data are organized as “collections”; typically patients’ imaging related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. Supporting data related to the images such as patient outcomes, treatment details, genomics and expert analyses are also provided when available.
The NDEx Project provides an open-source framework where scientists and organizations can share, store, manipulate, and publish biological network knowledge. The NDEx Project maintains a free, public website; alternatively, users can also decide to run their own copies of the NDEx Server software in cases where the stored networks must be kept in a highly secure environment (such as for HIPAA compliance) or where high application load is incompatible with a shared public resource.
The IMEx consortium is an international collaboration between a group of major public interaction data providers who have agreed to share curation effort and develop and work to a single set of curation rules when capturing data from both directly deposited interaction data or from publications in peer-reviewed journals, capture full details of an interaction in a “deep” curation model, perform a complete curation of all protein-protein interactions experimentally demonstrated within a publication, make these interaction available in a single search interface on a common website, provide the data in standards compliant download formats, make all IMEx records freely accessible under the Creative Commons Attribution License