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Found 44 result(s)
Country
The population-based cancer registries in each German federal state transfer data to the German Centre for Cancer Registry Data, as required by the Federal Cancer Registry Data Act. These data are combined, quality-checked, analysed and evaluated, and the results published in collaboration with the public health institutions of the federal states.
Country
The Australian Breast Cancer Tissue Bank (ABCTB) provides data contributed by an Australian network of cancer clinicians, researchers, and patients. ABCTB privacy protection policy ensures patients' identities are not revealed and cancer researchers are the only individuals with open access to data.
The Netherlands Cancer Registry is the national registration since 1989, providing statistics on cancer in the Netherlands. The registry is maintained by the Netherlands Comprehensive Cancer Organisation (IKNL). Data on incidence, prevalence, survival, mortality can be viewed in NCR data & figures on the IKNL website.
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.
Content type(s)
NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.
The Progenetix database provides an overview of copy number abnormalities in human cancer from currently 32548 array and chromosomal Comparative Genomic Hybridization (CGH) experiments, as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. The cancer profile data in Progenetix was curated from 1031 articles and represents 366 different cancer types, according to the International classification of Diseases in Oncology (ICD-O).
The information in the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer relates cytogenetic changes and their genomic consequences, in particular gene fusions, to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature by Felix Mitelman in collaboration with Bertil Johansson and Fredrik Mertens.
Content type(s)
>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
<<<!!!<<< The NCI CBIIT instance of the NBIA application was retired in March 2022. All data in the application has been transferred to The Cancer Image Archive https://www.re3data.org/repository/r3d100011559 and is available via the Access the Data > Search Radiology Portal menu item. The NBIA software is now maintained on GitHub, and can be built and deployed with the latest improvements and fixes that have been completed for TCIA. >>>!!!>>>
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.
St. Jude Cloud, an initiative of St. Jude Children's Research Hospital, provides data and analysis resources to the global research community. Our goal is to empower researchers across the world to advance cures for pediatric cancer and other pediatric catastrophic diseases.
<<<!!!<<< As of Aug. 15, 2019, we are suspending plasmid distribution from the collection. If you would like to request BioPlex ORF clones (Harper lab) or if you identify other clones in our collection for which you cannot find an alternative, please email us at plasmidhelp@hms.harvard.edu. >>>!!!>>>
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Country
<<<!!!<<< 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 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.
Country
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).
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.
Country
We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes.For both Chromatin- immunoprecipation Transcription Factors and Histone modifications. Sequence files and the associated probability files are also provided.
Country
!!! <<< 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) <<< !!! Using serial analysis of gene expression (SAGE) and microarrays, we are examining total mRNA populations in all developmental stages, both in whole worms and in specific cells and tissues. In addition, we are building promoter::GFP constructs to monitor gene expression in transgenic worms, focusing on C. elegans genes that have human orthologues. Also available are web-based PCR primer design tools, and access to information about our C. elegans Fosmid library.
Country
The German National Cohort (NAKO) has been inviting men and women aged between 20 and 69 to 18 study centers throughout Germany since 2014. The participants are medically examined and questioned about their living conditions. The GNC’s aim is to investigate the causes of chronic diseases, such as cancer, diabetes, cardiovascular diseases, rheumatism, infectious diseases, and dementia in order to improve prevention, early diagnoses and treatment of these very widely spread diseases.