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Found 46 result(s)
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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.
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>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed.
The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative.
CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month.
As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive.
The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there.
The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<<
The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects.
Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.
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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.
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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.
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- Statistics and Econometrics
- Economic and Social Policy
- Epidemiology, Medical Biometry, Medical Informatics
- Public Health, Health Services Research, Social Medicine
- Hematology, Oncology, Transfusion Medicine
- Economics
- Social and Behavioural Sciences
- Humanities and Social Sciences
- Medicine
- Medicine
- Life Sciences
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A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
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>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
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Oral Cancer Gene Database is an initiative of the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai. The present database, version II, consists of 374 genes. It is developed as a user friendly site that would provide the scientist, information and external links from one place. The database is accessed through a list of all genes, and Keyword Search using gene name or gene symbol, chromosomal location, CGH (in %), and molecular weight. Interaction Network shows the interaction between genes for particular biological processes and molecular functions.
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The repository is no longer available. <<<!!!<<< CPDB is retired >>>!!!>>>
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CaPSURE™ is a longitudinal, observational study of approximately 15,000 men with all stages of biopsy-proven prostate cancer. Patients have enrolled at 43 community urology practices, academic medical centers, and VA hospitals throughout the United States since 1995.
CEASAR stands for Comparative Effectiveness Analysis of Surgery and Radiation. The ongoing goal of CEASAR is to help learn more about what prostate cancer treatments work best, for which patients, in whose hands.
There are currently about 3,600 men with a prostate cancer diagnosis participating in CEASAR. Three rounds of surveys have been completed, with the first carried out in the spring of 2010. We are currently in the process of conducting our fourth survey with the same group of men in our study. This survey, our Three Year Follow-up, will occur throughout the summer of 2014.
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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).
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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.
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Born of the desire to systematize analyses from The Cancer Genome Atlas pilot and scale their execution to the dozens of remaining diseases to be studied, GDAC Firehose now sits atop terabytes of analysis-ready TCGA data and reliably executes thousands of pipelines per month. More information: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/
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<<<!!!<<< This repository is no longer available >>>!!!>>>
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The European Prospective Investigation into Cancer and Nutrition (EPIC) study is one of the largest cohort studies in the world, with more than half a million (521 000) participants recruited across 10 European countries and followed for almost 15 years.
EPIC was designed to investigate the relationships between diet, nutritional status, lifestyle and environmental factors, and the incidence of cancer and other chronic diseases. EPIC investigators are active in all fields of epidemiology, and important contributions have been made in nutritional epidemiology using biomarker analysis and questionnaire information, as well as genetic and lifestyle investigations.
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Exposome-Explorer is the first database dedicated to biomarkers of exposure to environmental risk factors for diseases. It contains detailed information on the nature of biomarkers, populations and subjects where measured, samples analyzed, methods used for biomarker analyses, concentrations in biospecimens, correlations with external exposure measurements, and biological reproducibility over time.
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The repository is no longer available. <<<!!!<<< Visit IRIS at EPA: https://www.epa.gov/iris >>>!!!>>>
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The CPTAC Data Portal is the centralized repository for the dissemination of proteomic data collected by the Proteome Characterization Centers (PCCs) for the CPTAC program. The portal also hosts analyses of the mass spectrometry data (mapping of spectra to peptide sequences and protein identification) from the PCCs and from a CPTAC-sponsored common data analysis pipeline (CDAP).
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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.
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FPC Mapping data files from species that have been fingerprinted at Canada's Michael Smith Genome Sciences Centre (BCGSC).
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CANJEM (CANadian Job-Exposure Matrix) is a large source of retrospective information on job-based exposure for a given occupation and time period. Covering most occupations and many agents, it provides information on the probability, frequency and intensity of exposure from a list of 258 occupational risk factors.
CANJEM was built from past individual expert evaluations of occupational exposures in a series of four case control studies of various cancers conducted since the mid-1980s up to 2010 in the greater Montreal area. During these studies over 30 000 jobs from 1930 to 2005 held by close to 10 000 subjects were evaluated by experts who assigned exposures based on descriptions of tasks, processes, work environment, and exposure control measures."
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<<<!!!<<< The 2019-2020 Questionnaire is no longer live. >>>!!!>>>
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CEEHRC represents a multi-stage funding commitment by the Canadian Institutes of Health Research (CIHR) and multiple Canadian and international partners. The overall aim is to position Canada at the forefront of international efforts to translate new discoveries in the field of epigenetics into improved human health. The two sites will focus on sequencing human reference epigenomes and developing new technologies and protocols; they will also serve as platforms for other CEEHRC funding initiatives, such as catalyst and team grants.
The complementary reference epigenome mapping efforts of the two sites will focus on a range of common human diseases. The Vancouver group will focus on the role of epigenetics in the development of cancer, including lymphoma and cancers of the ovary, colon, breast, and thyroid. The Montreal team will focus on autoimmune / inflammatory, cardio-metabolic, and neuropsychiatric diseases, using studies of identical twins as well as animal models of human disease.
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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).
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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.
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<<<!!!<<< This repository is no longer available. >>>!!!>>>
- Current projects
- EOSC FAIR-IMPACT
- re3data COREF
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Except where otherwise noted, content on this site is licensed under a
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-04-19
