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https://pdc.cancer.gov/pdc/

Portal to make cancer related proteomic datasets easily accessible to public. Facilitates multiomic integration in support of precision medicine through interoperability with other resources. Developed to advance our understanding of how proteins help to shape risk, diagnosis, development, progression, and treatment of cancer. One of several repositories within NCI Cancer Research Data Commons which enables researchers to link proteomic data with other data sets (e.g., genomic and imaging data) and to submit, collect, analyze, store, and share data throughout cancer data ecosystem. PDC provides access to highly curated and standardized biospecimen, clinical, and proteomic data, intuitive interface to filter, query, search, visualize and download data and metadata. Provides common data harmonization pipeline to uniformly analyze all PDC data and provides advanced visualization of quantitative information. Cloud based (Amazon Web Services) infrastructure facilitates interoperability with AWS based data analysis tools and platforms natively. Application programming interface (API) provides cloud-agnostic data access and allows third parties to extend functionality beyond PDC. Structured workspace that serves as private user data store and also data submission portal. Distributes controlled access data, such as patient-specific protein fasta sequence databases, with dbGaP authorization and eRA Commons authentication.

Proper citation: Proteomic Data Commons (RRID:SCR_018273) Copy   

•   Source: SciCrunch Registry

http://cahub.cancer.gov/about/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. A national center for biospecimen science and standards to advance cancer research and treatment. It was created in response to the critical and growing need for high-quality, well-documented biospecimens for cancer research. The initiative builds on resources already developed by the NCI, including the Biospecimen Research Network and the NCI Best Practices for Biospecimen Resources, both of which were developed to address challenges around standardization of the collection and dissemination of quality biospecimens. caHUB will develop the infrastructure for collaborative biospecimen research and the production of evidence-based biospecimen standard operating procedures.

Proper citation: caHUB (RRID:SCR_009657) Copy   

•   Source: SciCrunch Registry

https://proteomics.cancer.gov/programs/cptac

Clinical proteomic tumor analysis consortium to systematically identify proteins that derive from alterations in cancer genomes and related biological processes, in order to understand molecular basis of cancer that is not possible through genomics and to accelerate translation of molecular findings into clinic. Operates through Proteome Characterization Centers, Proteogenomic Translational Research Centers, and Proteogenomic Data Analysis Centers. CPTAC investigators collaborate, share data and expertise across consortium, and participate in consortium activities like developing standardized workflows for reproducible studies.

Proper citation: CPTAC (RRID:SCR_017135) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/cageneindex/Cancer+Gene+Index+End+User+Documentation

THIS RESOURCE IS NO LONGER IN SERVICE, documented on November 17, 2016. A database of genes that have been experimentally associated with human cancer diseases and/or pharmacological compounds, the evidence of these associations, and relevant annotations on the data.

Proper citation: Cancer Gene Index (RRID:SCR_001117) Copy   

•   Source: SciCrunch Registry

https://brd.cancer.gov/

Database to find literature, established protocols, and best practices for collecting, storing, and handling biological samples. Its main purpose is to help researchers improve the quality and reproducibility of biospecimen-based medical and genetic research. Provides a library of validated protocols that laboratories use to properly process human biospecimens (like blood or tissue) without degrading their molecular integrity. Offers procedural guidelines (BEBPs) backed by scientific literature to protect samples from pre-analytical variables (e.g., storage temperature, time-to-freezing). Catalogs thousands of peer-reviewed articles focused on biospecimen science.

Proper citation: Biospecimen Research Database (RRID:SCR_001944) Copy   

•   Source: SciCrunch Registry

http://primerdepot.nci.nih.gov/

A database that provides quantitative real time (qRT) PCR primers for 99.96% human RefSeq sequences. For 99% of intron-bearing genes, the PCR product will cross an exon-exon border which overlaps one of the largest introns. Primers are assumed to have a uniform annealing temperature of 60C, allowing them to be used in large-scale assays.

Proper citation: qPrimerDepot (RRID:SCR_003469) Copy   

•   Source: SciCrunch Registry

http://ncim.nci.nih.gov/ncimbrowser/

A wide-ranging biomedical terminology database that covers most terminologies used by NCI for clinical care, translational and basic research, and public information and administrative activities. NCIm features: * Maps 4,000,000 terms from more than 75 sources into 2,000,000 biomedical concepts that represent their meaning. * Displays preferred terms, synonyms, definitions, and other information from each source. * Links to NCI Thesaurus and other related information sources. * Contains 22,000,000 cross-links between content elements. * Updated frequently by a team of biomedical terminology and subject matter experts. NCIm contains most public domain terminologies from the National Library of Medicine's UMLS Metathesaurus, as well as many other biomedical terminologies created by or of interest to NCI and its partners. Some propriety terminologies are included, with permission, and have restrictions on their use. The current version of the NCI Metathesaurus, based on the UMLS build 2013AA, covers up to National Cancer Institute Thesaurus, 13.12d. A viewer for the UMLS changes document can be downloaded.

Proper citation: NCI Metathesaurus (RRID:SCR_003565) Copy   

•   Source: SciCrunch Registry

https://healthcaredelivery.cancer.gov/seermedicare/

Portal to reflect the linkage of two large population based sources of data that provide detailed information about Medicare beneficiaries with cancer.

Proper citation: NCI Division of Cancer Control and Population Sciences SEER-Medicare Linked Data Resource (RRID:SCR_025811) Copy   

•   Source: SciCrunch Registry

https://seer.cancer.gov/analysis/stage.html

Portal provides links to documentation for several stage variables that are available in the SEER data for analysis.

Proper citation: NCI SEER Cancer Stage Variable Documentation (RRID:SCR_025809) Copy   

•   Source: SciCrunch Registry

https://crtp.ccr.cancer.gov/sf/

Provides access to the latest technologies, with consultation and services available throughout the design and execution of sequencing projects.

Proper citation: NIH Center for Cancer Research Sequencing Core Facility (RRID:SCR_026840) Copy   

•   Source: SciCrunch Registry

http://linus.nci.nih.gov/BRB-ArrayTools.html

An integrated software package for the visualization and statistical analysis of DNA microarray gene expression data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BRB-ArrayTools (RRID:SCR_010938) Copy   

•   Source: SciCrunch Registry

http://dcb.nci.nih.gov/

http://dcb.nci.nih.gov/

Proper citation: Division of cancer biology and diagnosis (RRID:SCR_011188) Copy   

•   Source: SciCrunch Registry

http://cancercontrol.cancer.gov/funding.html

http://cancercontrol.cancer.gov/funding.html

Proper citation: Division of cancer control and population science (RRID:SCR_011189) Copy   

•   Source: SciCrunch Registry

http://helixweb.nih.gov/dnaworks

DNAWorks automates the design of oligonucleotides for gene synthesis by PCR-based methods. The availability of sequences of entire genomes has dramatically increased the number of protein targets, many of which will need to be overexpressed in cells other than the original source of DNA. Gene synthesis often provides a fast and economically efficient approach. The synthetic gene can be optimized for expression and constructed for easy mutational manipulation without regard to the parent genome. DNAWorks accesses a computer program that automates the design of oligonucleotides for gene synthesis. The website provides forms for simple input information, i.e. amino acid sequence of the target protein and melting temperature (needed for the gene assembly) of synthetic oligonucleotides. The program outputs a series of oligonucleotide sequences with codons optimized for expression in an organism of choice. Those oligonucleotides are characterized by highly homogeneous melting temperatures and a minimized tendency for hairpin formation. The approach presented here simplifies the production of proteins from a wide variety of organisms for genomics-based studies.

Proper citation: DNAWorks at Helix Systems (RRID:SCR_008470) Copy   

•   Source: SciCrunch Registry

http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CTCAE

A coding system for reporting adverse events that occur in the course of cancer therapy. It was derived from the Common Toxicity Criteria (CTC) v2.0 and is maintained by the Cancer Therapy Evaluation Program (CTEP) at the National Cancer Institution (NCI).

Proper citation: Common Terminology Criteria for Adverse Events (RRID:SCR_010296) Copy   

•   Source: SciCrunch Registry

http://variation.osu.edu/rtcgd/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of high throughput insertional mutagenesis screening projects of retroviral and transposon insertional mutagenesis in mouse tumors. Information in the RTCGD is obtained from sequence comparison by using public databases UCSC genome mm9 browser. Data based on previous genome assembly mm8 is also available at RTCGD mm8. MCGP has developed three web search tools including Easy Search to query proviral integration sites using mouse gene symbol of gene name; Model Search to obtain RIS information based on tumor models and/or tumor types; Interaction Search to find gene-to-gene interaction. It displays the list of genes which reside in the same tumor to your gene of interest.

Proper citation: Retroviral Tagged Cancer Gene Database (RRID:SCR_007908) Copy   

•   Source: SciCrunch Registry

http://genewindow.nci.nih.gov/

Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible

Proper citation: GeneWindow (RRID:SCR_008183) Copy   

•   Source: SciCrunch Registry

http://seer.cancer.gov/

SEER collects cancer incidence data from population-based cancer registries covering approximately 47.9 percent of the U.S. population. The SEER registries collect data on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, and first course of treatment, and they follow up with patients for vital status.There are two data products available: SEER Research and SEER Research Plus. This was motivated because of concerns about the increasing risk of re-identifiability of individuals. The Research Plus databases require more rigorous process for access that includes user authentication through Institutional Account or multiple-step request process for Non-Institutional users.

Proper citation: Surveillance Epidemiology and End Results (RRID:SCR_006902) Copy   

•   Source: SciCrunch Registry

https://cgwb.nci.nih.gov/goldenPath/bamview/documentation/index.html

A variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. Bambino may be launched online via Java Web Start or downloaded and run locally.

Proper citation: Bambino (RRID:SCR_005649) Copy   

•   Source: SciCrunch Registry