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https://seer.cancer.gov/csr/1975_2016/

Platform to report outlining trends in cancer statistics and methods to derive various cancer statistics from the Surveillance, Epidemiology, and End Results (SEER) program. Authoritative source for cancer statistics in the United States.

Proper citation: NCI SEER Cancer Statistics Review (RRID:SCR_024685) Copy   

•   Source: SciCrunch Registry

https://seer.cancer.gov/lymphomarecode/lymphoma-2020.html

Website describing International Classification of Diseases codes that corresponds to lymphomas in the Surveillance, Epidemiology, and End Results (SEER) registry.

Proper citation: NCI Lymphoid Neoplasm Recode 2020 Revision Definition (RRID:SCR_024686) Copy   

•   Source: SciCrunch Registry

https://openmm.org/

Software toolkit to run modern molecular simulations. It can be used either as a standalone application for running simulations, or as a library that enables accelerated calculations for molecular dynamics on high-performance computer architectures.

Proper citation: OpenMM (RRID:SCR_000436) Copy   

•   Source: SciCrunch Registry

http://www.karmanos.org/

Center for patient care, education and research on cancer. The institute focuses its research on prevention methods, early detection, treatment and finding cures.

Proper citation: Karmanos Cancer Institute (RRID:SCR_000508) Copy   

•   Source: SciCrunch Registry

http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

•   Source: SciCrunch Registry

http://dctd.cancer.gov/

Division of NCI that takes prospective cancer detection and treatment leads, facilitates their paths to clinical application, and expedites the initial and subsequent large-scale testing of new agents, biomarkers, imaging tests, and other therapeutic interventions (radiation, surgery, immunotherapy) in patients. DCTD, like all of NCI, supports many programs that could not be done without government funding - investigators supported by the division engage in scientifically sound, high-risk research that may yield great benefits for patients with cancer, but are too difficult or risky for industry or academia to pursue. This includes a particular emphasis on the development of distinct molecular signatures for cancer, refined molecular assays, and state-of-the-art imaging techniques that will guide oncologic therapy in the future. The division has eight major programs that work together to bring unique molecules, diagnostic tests, and therapeutic interventions from the laboratory bench to the patient bedside: * Cancer Diagnosis Program * Cancer Imaging Program * Cancer Therapy Evaluation Program * Developmental Therapeutics Program * Radiation Research Program * Translational Research Program * Biometrics Research Branch * Office of Cancer Complementary and Alternative Medicine

Proper citation: DCTD (RRID:SCR_004196) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/annotare/

A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.

Proper citation: Annotare (RRID:SCR_000319) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/nondetects.html

Software R package to model and impute non-detects in results of qPCR experiments.Used to directly model non-detects as missing data.

Proper citation: nondetects (RRID:SCR_001702) Copy   

•   Source: SciCrunch Registry

http://www.pathology.med.ohio-state.edu/HTRN/apc/default.asp

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The Adenoma Polyp Tissue Bank (APTB) receives whole blood from patients enrolled in the Prevention of Sporadic Colorectal Adenomas with Celecoxib clinical trial. We have reached our accrual on blood submissions, so we will no longer be receiving blood specimens The objectives of this trial are as follows: A. To determine the efficacy and safety of celecoxib versus placebo in preventing the occurrence of newly detected colorectal adenomas in subjects at increased risk for colorectal carcinoma. In addition to incidence, other established risk factors will be evaluated for their association with occurrence of new colorectal adenomas, including cancer family history and adenoma size, histopathologic grade, multiplicity and location. Primary assessment of treatment efficacy will be the reduction in the number of subjects with adenomas at colonoscopy after Year 1 and Year 3 of study drug use. Secondary assessments of treatment efficacy will be 1) the number of adenomas 2) the histopathologic grade of adenomas and 3) the size of adenomas, also measured after one year and three years of study drug use. These factors will be incorporated into a risk model for predicting adenoma occurrence and response to celecoxib. B. To determine the efficacy of celecoxib versus placebo in modulating one or more of a panel of biomarkers for colorectal cancer at the cellular and molecular level sampled in a subset of subjects at selective sites at baseline and after Year 1 and Year 3 of study drug use. These biomarkers will include measurements of aberrant crypt foci (ACF), proliferation (index and crypt distribution), apoptosis (index and crypt distribution), COX expression and activity. If modulation of one or more mucosal biomarkers occur, we will explore whether it correlates with the development of incident colorectal neoplasia (adenomas/carcinomas), thereby attempting to validate the surrogacy of that biomarker. C. To develop a specimen bank. Serum and white blood cells are isolated from whole blood and adenoma tissue blocks and slides are banked. Banked specimens will become available for use in correlative science studies at a later point. This project began in 1999 and will be extended through 2006. The lead principal investigator is Monica M. Bertagnolli, MD, Brigham and Women''s Hospital, Boston, MA, and the APTB Director is Scott Jewell, Ph.D., Department of Pathology, The Ohio State University. The APTB is supported by the NIH, NCI Division of Cancer Prevention, in connection with the Strang Cancer Prevention Center, Cornell University, New York., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Adenoma Polyp Tissue Bank (RRID:SCR_005366) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

•   Source: SciCrunch Registry

http://www.bionet.umn.edu/tpf/home.html

Procure and distribute human tissue and other biological samples in support of basic, translational, and clinical cancer research at the University of Minnesota. The TPF is a centralized resource with standardized patient consent, sample collection, processing, storage, quality control, distribution, and electronic record maintenance. Since the 1996 inception of the TPF, over 61,000 tissue samples including well-preserved samples of malignant and benign tumors, organ-matched normal tissue, and other types of diseased tissues, have been collected from surgical specimens obtained at the University of Minnesota Medical Center-Fairview (UMMC-F) University Campus. Surgical pathologists are intellectually engaged in TPF functions, providing researchers with specimen-oriented medical consultation to facilitate research productivity. Prior to surgery, TPF personnel identify and consent patients for procurement of tissue, blood, urine, saliva, and ascites fluid. Within the integrated working environment of the surgical pathology laboratory, freshly obtained tissues not needed for diagnosis are selected and provided by pathologists to TPF personnel. Tissue samples are then assigned an independent code and processed. TPF staff can also work with researchers to individualize the procurement of tissues to fit specific research needs.

Proper citation: University of Minnesota Tissue Procurement Facility (RRID:SCR_004270) Copy   

•   Source: SciCrunch Registry

http://acsr.ucsf.edu/

A biorepository for HIV-infected human biospecimens from a wide spectrum of HIV-related or associated diseases, including cancer, and from appropriate HIV-negative controls. The ACSR has formalin-fixed paraffin embedded biospecimens, fresh frozen biospecimens, malignant cell suspensions, fine needle aspirates, and cell lines from patients with HIV-related malignancies. It also contains serum, plasma, urine, bone marrow, cervical and anal specimens, saliva, semen, and multi-site autopsy speicmens from patients with HIV-related malignancies including those who have participated in clinical trials. The ACSR has an associated databank that contains prognostic, staging, outcome and treatment data on patients from whom tissues were obtained. The ACSR database contains more than 300,000 individual biospecimens with associated clinical information. Biospecimens are entered into the ACSR database by processing type, disease category, and number of cases defined by disease category.

Proper citation: AIDS and Cancer Specimen Resource (RRID:SCR_004216) Copy   

•   Source: SciCrunch Registry

http://pluto3.nci.nih.gov/tissue/default.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Specimen Resource Locator is a database to help researchers locate human specimens (tissue, serum, DNA/RNA, other specimens) for cancer research. It includes tissue banks and tissue procurement systems with access to normal, benign, precancerous and cancerous human tissue from a variety of organs. Researchers specify the types of specimens, number of cases, preservation methods and associated data they require. The Locator will then search the database and return a list of tissue resources most likely to meet their requirements. When no match is obtained, the researcher is referred to the NCI Tissue Expediter ([email protected]). The Tissue expediter is a scientist who can help researchers identify appropriate resources and/or appropriate collaborators.

Proper citation: NCI Specimen Resource Locator (RRID:SCR_004754) Copy   

•   Source: SciCrunch Registry

http://www.nsabp.pitt.edu/NSABP_Pathology.asp

The NSABP (National Surgical Adjuvant Breast and Bowel Project) Tissue Bank is the central repository of tissue samples (stained and unstained slides, tissue blocks, and frozen tissue specimens) collected from clinical trials conducted by the NSABP. The main scientific aim of the NSABP Division of Pathology is to develop clinical context-specific prognostic markers and predictive markers that predict response to or benefit from specific therapeutic modality. To achieve this aim, the laboratory collects the tumor and adjacent normal tissues from cancer patients enrolled into the NSABP trials through its membership institutions, and maintain these valuable materials with clinical follow-up information and distribute them to qualified approved investigators. Currently, specimens from more than 90,000 cases of breast and colon cancer are stored and maintained at the bank. Paraffin embedded tumor specimens are available from NSABP trials. We currently do not bank frozen tissues. All blocks are from patients enrolled in prospective NSABP treatment protocols and complete clinical follow up information as well as demographic information is available. Depending on the project, unstained tissue sections of 4-micrometer thickness, tissue microarrays, or stained slides are provided to the investigators in a blinded study format. Any investigators with novel projects that conform to the research goals of NSABP may apply for the tissue. Please refer to the NSABP Tissue Bank Policy to determine if your project conforms to these goals. Priority is given to NSABP membership institutions who regularly submit tissue blocks.

Proper citation: National Surgical Adjuvant Breast and Bowel Project Tissue Bank (RRID:SCR_004506) Copy   

•   Source: SciCrunch Registry

https://genome-cancer.ucsc.edu/

A suite of web-based tools to visualize, integrate and analyze cancer genomics and its associated clinical data. It is possible to display your own clinical data within one of their datasets.

Proper citation: UCSC Cancer Genomics Browser (RRID:SCR_011796) Copy   

•   Source: SciCrunch Registry

http://cbbiweb.uthscsa.edu/KMethylomes/

Datbase and web-based system for visualization and analysis of genome-wide methylation data of human cancers.

Proper citation: Cancer Methylome System (RRID:SCR_012013) Copy   

•   Source: SciCrunch Registry

http://www.cravat.us/

A web-based application designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis.

Proper citation: CRAVAT (RRID:SCR_012776) Copy   

•   Source: SciCrunch Registry

https://www.gem-beta.org/Public/Home.aspx

Database that contains behavioral and social science measures organized by theoretical constructs. GEM is designed to enable researchers to use common measures with the goal of exchanging harmonized data.

Proper citation: Grid-Enabled Measures Database (RRID:SCR_016043) Copy   

•   Source: SciCrunch Registry

https://rtips.cancer.gov/rtips/index.do

Database of cancer control interventions and program materials. It is designed to provide program planners and public health practitioners easy and immediate access to research-tested materials.

Proper citation: Research-tested Intervention Programs (RTIPs) (RRID:SCR_016042) Copy   

•   Source: SciCrunch Registry

https://www.clinicalgenome.org

Genomics knowledgebase for clinical relevance of genes and variants for use in research. ClinGen's primary function is to store and share information for the benefit of the scientific community. Laboratory scientists, clinicians, and patients can share and access data.

Proper citation: ClinGen (RRID:SCR_014968) Copy   

•   Source: SciCrunch Registry