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Found 122 result(s)
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
Patient Reported Outcomes Following Initial treatment and Long term Evaluation of Survivorship (PROFILES)’ is a registry for the study of the physical and psychosocial impact of cancer and its treatment from a dynamic, growing population-based cohort of both short and long-term cancer survivors. Researchers from the Netherlands Comprehensive Cancer Centre and Tilburg University in Tilburg, The Netherlands, work together with medical specialists from national hospitals in order to setup different PROFILES studies, collect the necessary data, and present the results in scientific journals and (inter)national conferences.
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.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
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>>>!!!<<< 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. >>>!!!>>>
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.
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.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
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The repository is no longer available. <<<!!!<<< Visit IRIS at EPA: https://www.epa.gov/iris >>>!!!>>>
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).
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. >>>!!!>>>
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HIstome: The Histone Infobase is a database of human histones, their post-translational modifications and modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics, Indian Institute of Science Education and Research (IISER), Pune.
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.
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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.
ITER is an Internet database of human health risk values and cancer classifications for over 680 chemicals of environmental concern from multiple organizations wordwide. ITER is the only database that presents risk data in a tabular format for easy comparison, along with a synopsis explaining differences in data and a link to each organization for more 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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ALEXA is a microarray design platform for 'alternative expression analysis'. This platform facilitates the design of expression arrays for analysis of mRNA isoforms generated from a single locus by the use of alternative transcription initiation, splicing and polyadenylation sites. We use the term 'ALEXA' to describe a collection of novel genomic methods for 'alternative expression' analysis. 'Alternative expression' refers to the identification and quantification of alternative mRNA transcripts produced by alternative transcript initiation, alternative splicing and alternative polyadenylation. This website provides supplementary materials, source code and other downloads for recent publications describing our studies of alternative expression (AE). Most recently we have developed a method, 'ALEXA-Seq' and associated resources for alternative expression analysis by massively parallel RNA sequencing.
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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."
CODEX is a database of NGS mouse and human experiments. Although, the main focus of CODEX is Haematopoiesis and Embryonic systems, the database includes a large variety of cell types. In addition to the publically available data, CODEX also includes a private site hosting non-published data. CODEX provides access to processed and curated NGS experiments. To use CODEX: (i) select a specialized repository (HAEMCODE or ESCODE) or choose the whole compendium (CODEX), then (ii) filter by organism and (iii) choose how to explore the database.
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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).