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http://www.cancer.gov/researchandfunding

Federal government agency for cancer research and training established in 1937. National Cancer Program is responsibility of NCI to coordinate, conduct and support research, training, health information dissemination with respect to cause, diagnosis, prevention, and treatment of cancer, rehabilitation from cancer, and continuing care of cancer patients and families of cancer patients. Supports construction of laboratories, clinics, and related facilities necessary for cancer research through award of grants.

Proper citation: National Cancer Institute (RRID:SCR_011176) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/

NIH is the nations medical research agency - making important medical discoveries that improve health and save lives. The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the primary Federal agency for conducting and supporting medical research. Helping to lead the way toward important medical discoveries that improve peoples health and save lives, NIH scientists investigate ways to prevent disease as well as the causes, treatments, and even cures for common and rare diseases. NIH research impacts: * child and teen health, * men's health, * minority health, * seniors' health, * women's health, and * wellness and lifestyle issues. Composed of 27 Institutes and Centers, the NIH provides leadership and financial support to researchers in every state and throughout the world.

Proper citation: National Institutes of Health (RRID:SCR_011417) Copy   

•   Source: SciCrunch Registry

http://cancercontrol.cancer.gov/tcrb/tturc/

A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.

Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. An initiative to develop a molecular classification schema that is both clinically and biologically meaningful, based on gene expression and genomic data from tumors (Gliomas) of patients who will be prospectively followed through natural history and treatment phase of their illness. The study will also explore gene expression profiles to determine the responsiveness of the patients and correlate with discrete chromosomal abnormalities. The initiative was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. The sample collection is accompanied by careful and prospective clinical data acquisition, allowing a variety of matched molecular and clinical data permitting a wide variety of analyses. GMDI has accrued fresh frozen tumors in the retrospective phase (all from the Henry Ford Hospital, without germline DNA) and fresh frozen tumors in the prospective phase (from a variety of institutions). In addition to characterizing the samples from patients enrolled in GMDI, the microarray group has generated genomic-scale analyses of the many human and canine glioma initiating cells/glioma stem cells (GIC/GSC) lines, as well as many canine and murine normal neural stem cell (NSC) lines produced in laboratory.

Proper citation: Glioma Molecular Dignostic Initiatives (RRID:SCR_003329) Copy   

•   Source: SciCrunch Registry

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

A software package for the visualization and statistical analysis of DNA microarray gene expression data. The tools have been developed from the R statistical system, in C and fortran programs and Java applications. They are integrated into Excel as an add-in.

Proper citation: Biometric Research Branch: ArrayTools (RRID:SCR_000778) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

•   Source: SciCrunch Registry

http://www3.cancer.gov/intra/dcs/dcshome.htm

http://www3.cancer.gov/intra/dcs/dcshome.htm

Proper citation: Division of clinical sciences (RRID:SCR_004787) Copy   

•   Source: SciCrunch Registry

http://dctd.cancer.gov/FundingPartnerships/PAsRFAs.htm

http://dctd.cancer.gov/FundingPartnerships/PAsRFAs.htm

Proper citation: Division of cancer treatment (RRID:SCR_004774) Copy   

•   Source: SciCrunch Registry

http://ccr.cancer.gov/staff/staff.asp?profileid=5637

This is the lab portal of Dr. Schiller at the National Cancer Institue in Frederick, Germany. Keyowrds: Cancer, REsearch, Institute, Laboratory,

Proper citation: Center for Cancer Research: Schiller Laboratory (RRID:SCR_012969) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/caGWAS/caGWAS

Too that allows researchers to integrate, query, report, and analyze significant associations between genetic variations and disease, drug response or other clinical outcomes. SNP array technologies make it possible to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously, enabling whole genome association studies. Within the Clinical Genomic Object Model (CGOM), the caIntegrator team created a domain model for Whole Genome Association Study Analysis. CGOM-caGWAS is a A semantically annotated domain model that captures associations between Study, Study Participant, Disease, SNP Association Analysis, SNP Population Frequency and SNP annotations. caGWAS APIs and web portal provide: * a semantically annotated domain model, database schema with sample data, seasoned middleware, APIs, and web portal for GWAS data; * platform and disease agnostic CGOM-caGWAS model and associated APIs; * the opportunity for developers to customize the look and feel of their GWAS portal; * a foundation of open source technologies; * a well-tested and performance-enhanced platform, as the same software is being used to house the CGEMS data portal; * accelerated analysis of results from various biomedical studies; and * a single application through which researchers and bioinformaticians can access and analyze clinical and experimental data from a variety of data types, as caGWAS objects are part of the CGOM, which includes microarray, genomic, immunohistochemistry, imaging, and clinical data.

Proper citation: caGWAS (RRID:SCR_009617) Copy   

•   Source: SciCrunch Registry

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

An instance of a Domain Analysis Model (DAM) with the goal of producing a shared view of the dynamic and static semantics for the domain of protocol-driven research and its associated regulatory artifacts. This domain of interest is further defined as: Protocol-driven research and its associated regulatory artifacts: i.e. the data, organization, resources, rules, and processes involved in the formal assessment of the utility, impact, or other pharmacological, physiological, or psychological effects of a drug, procedure, process, or device on a human, animal, or other subject or substance plus all associated regulatory artifacts required for or derived from this effort, including data specifically associated with post-marketing adverse event reporting. The Biomedical Research Integrated Domain Group (BRIDG) Model is a collaborative effort engaging stakeholders from the Clinical Data Interchange Standards Consortium (CDISC), the HL7 Regulated Clinical Research Information Management Technical Committee (RCRIM TC), the National Cancer Institute (NCI) and its Cancer Biomedical Informatics Grid (caBIG??), and the US Food and Drug Administration (FDA). Source repository: https://ncisvn.nci.nih.gov/WebSVN/listing.php?repname=bridg-model&path=%2Ftrunk%2FModel+-+OWL%2F&

Proper citation: Biomedical Research Integrated Domain Group Model (RRID:SCR_010265) Copy   

•   Source: SciCrunch Registry

http://cancer.gov/cancertopics/pdq/cancerdatabase

NCI''s comprehensive cancer database that contains summaries on a wide range of cancer topics; a registry of 8,000+ open and 19,000+ closed cancer clinical trials from around the world; a directory of professionals who provide genetics services; the NCI Dictionary of Cancer Terms, with definitions for 6,800+ cancer and medical terms; and the NCI Drug Dictionary, which has information on 2,300+ agents used in the treatment of cancer or cancer-related conditions. The PDQ cancer information summaries are peer reviewed and updated monthly by six editorial boards comprised of specialists in adult treatment, pediatric treatment, supportive care, screening and prevention, genetics, and complementary and alternative medicine. The Boards review current literature from more than 70 biomedical journals, evaluate its relevance, and synthesize it into clear summaries. Many of the summaries are also available in Spanish.

Proper citation: Physician Data Query (RRID:SCR_006833) Copy   

•   Source: SciCrunch Registry

http://snp500cancer.nci.nih.gov

It provides a central resource for sequence verification of SNPs. The goal of the SNP500Cancer project is to resequence 102 reference samples to find known or newly discovered single nucleotide polymorphisms (SNPs) which are of immediate importance to molecular epidemiology studies in cancer. The site allows users to search for SNPs using SNP identifier, gene symbol, gene alias, chromosome location, or gene ontology pathway.

Proper citation: SNP500Cancer (RRID:SCR_007943) Copy   

•   Source: SciCrunch Registry

http://web.ncifcrf.gov/rtp/GEL/primerdb/default.asp

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. It provides information about primers and probes that can be used to quantitate human and mouse mRNA by reverse transcription polymerase chain reaction (RTx96PCR) assays. Users can search the QPPD to find: * Primer sets and probes for a given gene * Primer location * Amplicon size * Assay type * Positions of single nucleotide polymorphisms (SNPs) * Literature references * Available I.M.A.G.E. cDNA clones * The Primer Viewer, a graphical representation of the gene and primer sets, which includes hyperlinks to Gene Info from the Cancer Gene Anatomy Project (CGAP) and the CGAP SNP viewer.

Proper citation: QPPD - Quantitative PCR Primer Database (RRID:SCR_007880) 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

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

http://epi.grants.cancer.gov/CFR/

The Breast Cancer Family Registry (Breast CFR) and the Colon Cancer Family Registry (Colon CFR) were established by the National Cancer Institute (NCI) as a unique resource for investigators to use in conducting studies on the genetics and molecular epidemiology of breast and colon cancer. Known collectively as the CFRs, they share a central goal: the translation of research to the clinical and prevention settings for the benefit of Registry participants and the general public. The CFRs are particularly interested in: * Identifying and characterizing cancer susceptibility genes; * Defining gene-gene and gene-environment interactions in cancer etiology; and * Exploring the translational, preventive, and behavioral implications of research findings. The CFRs do not provide funding for studies; however, researchers can apply to access CFR data and biospecimens contributed by thousands of families from across the spectrum of risk for these cancers and from population-based or relative controls. Special features of the CFRs include: * Population-based and clinic-based ascertainment; * Systematic collection of validated family history; * Epidemiologic risk factor , clinical, and followup data; * Biospecimens (including tumor blocks and Epstein-Barr virus (EBV)-transformed cell lines); * Ongoing molecular characterization of the participating families; and * A combined informatics center.

Proper citation: NCI Breast and Colon Cancer Family Registries (RRID:SCR_006664) Copy   

•   Source: SciCrunch Registry