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http://www.cancergenomics.org/

Consortium promoting communication and collaboration among cancer cytogenomics laboratories, who are interested in applying microarray technologies to cancer diagnosis and cancer research. Their oals are to (1) establish platform-neutral and cancer specific microarray designs for diagnostic purposes, (2) share cancer microarray data between participating institutions for education purposes, (3) create a public cancer array database, and (4) carry out multicenter cancer genome translational research. Collaboration amongst the different laboratories and researchers will not only provide validation for the microarray design(s) but ultimately provide more comprehensive molecular information and more accurate interpretation to better serve cancer patients and further cancer research. The CGC was officially incorporated in June 2010 as a not-for-profit organization.

Proper citation: Cancer Genomics Consortium (RRID:SCR_002384) Copy   

•   Source: SciCrunch Registry

http://hardinmd.lib.uiowa.edu/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. A medical database with lists, or directories, of information in health and medicine and images of medical conditions. Users may search Hardin MD, browse through the Medical picture gallery, and sort search results by disease or alphabetical letter.

Proper citation: Hardin MD (RRID:SCR_002364) Copy   

•   Source: SciCrunch Registry

https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. 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. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

•   Source: SciCrunch Registry

https://www.bigtencrc.org/

A consortium that aims to transform cancer research through collaborative oncology trials that leverage the scientific and clinical expertise of the Big Ten universities. The goal is to align the conduct of cancer research through collaborative, hypothesis-driven, highly translational oncology trials that leverage the scientific and clinical expertise. The clinical trials that will be developed will be linked to molecular diagnostics, enabling researchers to understand what drives the cancers to grow and what might be done to stop them from growing. The consortium also leverages geographical locations and existing relationships among the cancer centers. One of the consortium's goals is to harmonize contracts and scientific review processes to expedite clinical trials. The consortium will only focus on phase 0 to II trials because larger trials - even a randomized phase II trial - are difficult to conduct at a single cancer center.

Proper citation: Big Ten Cancer Research Consortium (RRID:SCR_004025) Copy   

•   Source: SciCrunch Registry

http://datacatalog.med.nyu.edu/

A searchable data catalog that facilitates researchers'' access to large datasets available either publicly or through institutional or individual licensing. Dataset records include information about the content of the dataset, how to access the dataset, and local experts within NYULMC and NYU to assist in the use of these datasets. The data catalog will expand to include internally generated datasets from NYULMC and NYU in the near future. Use the contact form if you are interested in submitting a dataset to the data catalog.

Proper citation: NYU Data Catalog (RRID:SCR_004012) Copy   

•   Source: SciCrunch Registry

http://www.cancerdiagnosis.nci.nih.gov/

National program to improve the diagnosis and assessment of cancer by moving scientific knowledge into clinical practice by coordinating and funding resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens. The Cancer Diagnosis Program is divided into four branches: Biorepository and Biospecimen Research Branch (BBRB), Diagnostic Biomarkers and Technology Branch (DBTB), Diagnostics Evaluation Branch (DEB), and the Pathology Investigation and Resources Branch (PIRB).

Proper citation: CDP (RRID:SCR_004236) Copy   

•   Source: SciCrunch Registry

https://www.bannerhealth.com/research/locations/sun-health-institute/programs/body-donation

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An autopsy-based, research-devoted brain bank, biobank and biospecimen bank that derives its human donors from the Arizona Study of Aging and Neurodegenerative Disease (AZSAND), a longitudinal clinicopathological study of the health and diseases of elderly volunteers living in Maricopa county and metropolitan Phoenix, Arizona. Their function is studied during life and their organs and tissue after death. To date, they have concentrated their studies on Alzheimer's disease, Parkinson's disease, heart disease and cancer. They share the banked tissue, biomaterials and biospecimens with qualified researchers worldwide. Registrants with suitable scientific credentials will be allowed access to a database of available tissue linked to relevant clinical information, and will allow tissue requests to be initiated., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Brain and Body Donation Program (RRID:SCR_004822) Copy   

•   Source: SciCrunch Registry

http://glioblastoma.alleninstitute.org/

Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.

Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy   

•   Source: SciCrunch Registry

https://www.saintluc.be/en/node/2561

An essential reference center in Europe and a leader in French-speaking Belgium that treats all types of adult and childhood cancer. They fight against cancer while giving patients comprehensive and humane care. Their quest for excellence is in three main academic fields: clinical care, research and teaching.

Proper citation: Cliniques Universitaires Saint-Luc Cancer Centre (RRID:SCR_004922) Copy   

•   Source: SciCrunch Registry

http://seer.cancer.gov/resources/

Portal provides SEER research data and software SEER*Stat and SEER*Prep. SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas can be used to examine stage at diagnosis by race/ethnicity, calculate survival by stage at diagnosis, age at diagnosis, and tumor grade or size, determine trends and incidence rates for various cancer sites over time. SEER releases new research data every Spring based on the previous November’s submission of data.

Proper citation: SEER Datasets and Software (RRID:SCR_003293) 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://purl.bioontology.org/ontology/CANONT

Upper-level ontology for cancer.

Proper citation: Upper-Level Cancer Ontology (RRID:SCR_010443) Copy   

•   Source: SciCrunch Registry

https://humantumoratlas.org

HTAN is National Cancer Institute funded Cancer Moonshot initiative to construct 3-dimensional atlases of dynamic cellular, morphological, and molecular features of human cancers as they evolve from precancerous lesions to advanced disease.Provides three dimensional atlases of cancer transitions for diverse set of tumor types. Efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at single point in time. Data portal for Human Tumor Atlas Network. Data available on HTAN Portal is open access. Certain data types with potential for re-identification are available in restricted access through dbGAP.

Proper citation: Human Tumor Atlas Network (RRID:SCR_023364) Copy   

•   Source: SciCrunch Registry

https://www.cancermodels.org/

Cancer research platform that aggregates clinical, genomic and functional data from various types of patient derived cancer models, xenographs, organoids and cell lines. Open catalog of harmonised patient-derived cancer models. Standardises, harmonises and integrates clinical metadata, molecular and treatment-based data from academic and commercial providers worldwide. Data is FAIR and underpins generation and testing of new hypotheses in cancer mechanisms and personalised medicine development. PDCM Finder have expanded to organoids and cell lines and is now called CancerModels.Org. PDCM Finder was launched in April 2022 as successor of PDX Finder portal, which focused solely on patient-derived xenograft models.

Proper citation: CancerModels.Org (RRID:SCR_023931) Copy   

•   Source: SciCrunch Registry

https://hints.cancer.gov/

Regularly collects nationally representative data about American public’s knowledge of, attitudes toward, and use of cancer and health related information. HINTS data are used to monitor changes in fields of health communication and health information technology and to create more effective health communication strategies across different populations. Weighted, nationally representative probability based survey of civilian, non-institutionalized adults administered by National Cancer Institute on knowledge of and attitudes toward cancer relevant information.

Proper citation: Health Information National Trends Survey (RRID:SCR_023943) Copy   

•   Source: SciCrunch Registry

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://ganjoho.jp/public/index.html

Portal provides information on Cancer Statistics in Japan. Official website operated by National Cancer Center for cancer information.

Proper citation: Cancer Information Service (RRID:SCR_024445) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

•   Source: SciCrunch Registry

http://sharedresources.fredhutch.org/core-facilities/bioinformatics

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Core provides bioinformatics specialists available to assist researchers with processing, exploring, and understanding genomics data.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Bioinformatics Resource (RRID:SCR_015324) Copy   

•   Source: SciCrunch Registry