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http://cancer3d.org

Database that allows for the exploration of cancer on somatic missense mutations from the Cancer Genome Atlas and Cancer Cell Line Encyclopedia. The site maps proteins and mutations using 3D models and is an interface to the algorithms e-Driver and e-Drug allowing for the prediction of novel cancer drivers or drug biomarkers.

Proper citation: Cancer3D (RRID:SCR_013755) Copy   

•   Source: SciCrunch Registry
  

https://ckb.jax.org/

Semi-automated and manually curated database of gene/variant annotations, therapy knowledge, diagnostic/prognostic information, and oncology clinical trials. Users can search CKB via gene, gene variants, drug, drug class, indication, and clinical trials.

Proper citation: Jackson Laboratory Clinical Knowledgebase (RRID:SCR_014965) Copy   

•   Source: SciCrunch Registry
  

https://www.jax.org/jax-mice-and-services/in-vivo-pharmacology/mouse-tumor-biology-database

Database supports use of mouse model system for human cancer by providing comprehensive resource for data and information on various tumor models.

Proper citation: Mouse Tumor Biology Database (RRID:SCR_006517) Copy   

•   Source: SciCrunch Registry
  

http://www.iiserpune.ac.in/~coee/histome/

Database of human histone variants, sites of their post-translational modifications and various histone modifying enzymes. The database covers 5 types of histones, 8 types of their post-translational modifications and 13 classes of modifying enzymes. Many data fields are hyperlinked to other databases (e.g. UnprotKB/Swiss-Prot, HGNC, OMIM, Unigene etc.). Additionally, this database also provides sequences of promoter regions (-700 TSS +300) for all gene entries. These sequences were extracted from the UCSC genome browser. Sites of post-translational modifications of histones were manually searched from PubMed listed literature. Current version contains information for about ~50 histone proteins and ~150 histone 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 (CoEE), Indian Institute of Science Education and Research (IISER), Pune.

Proper citation: HIstome: The Histone Infobase (RRID:SCR_006972) 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
  

http://ercsb.ewha.ac.kr:8080/FusionGene/

Knowledgebase of fusion transcripts collected from various public resources such as the Sanger CGP, OMIM, PubMed, and Mitelman's database. It is an alignment viewer to facilitate examining reliability of fusion transcripts and inferring functional significance., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ChimerDB (RRID:SCR_007596) Copy   

•   Source: SciCrunch Registry
  

http://www.cta.lncc.br/

A database of information about each Cancer-Testis (CT) gene, its gene products and the immune response induced in cancer patients by these proteins. CT antigens are proteins normally expressed only in the human germ line but that are also present in a significant subset of malignant tumors. The practical importance of these proteins is that due to their restricted expression pattern they are frequently recognized by the immune system of cancer patients. Moreover, this antigenicity has raised the possibility of their being used as vaccines to actively stimulate immune responses in order to combat tumor growth. As a result worldwide research into many aspects of CT antigens is rapidly growing prompting the construction of this database as a resource for investigators involved in this area.

Proper citation: CTDatabase (RRID:SCR_007614) Copy   

•   Source: SciCrunch Registry
  

http://driverdb.ym.edu.tw/DriverDB/intranet/init.do

A database for cancer driver gene/mutation that incorporates a huge amount of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic), and published bioinformatics algorithms dedicated to driver gene/mutation identification.

Proper citation: DriverDB (RRID:SCR_007736) Copy   

•   Source: SciCrunch Registry
  

http://research-public.gene.com/Research/genentech/canpredict/index.html

Web application that uses a combination of computational methods to identify those changes most likely to be cancer-associated.

Proper citation: CanPredict (RRID:SCR_008216) Copy   

•   Source: SciCrunch Registry
  

https://med.stanford.edu/lucasmri.html

Biomedical technology research center that develops innovative technologies in five core research areas of magnetic resonance imaging and spectroscopy (MRI/MRS): # image reconstruction, fast imaging and radiofrequency (RF) pulse design methods, # R hardware development, # body imaging methods, # neuroimaging methods. # MR spectroscopy methods. In each of these areas, they capitalize on the long-standing, successful partnership and extensive experience in Stanford's Radiology and Electrical Engineering departments to improve and expand imaging technology for use in basic research and clinical care, and to provide cutting edge opportunities to the extramural community for biomedical research with MRI. Over its more than 18 years of existence, CAMRT has been motivated by and has served a wide base of extramurally sponsored collaborators and service users from leading medical and research institutions. Examples of collaborative projects are the development of real-time functional MRI biofeedback methods for neuroscience and clinical applications such as pain remediation, development of methods to mitigate metal artifacts in musculoskeletal imaging, development of novel RF pulses for many applications, and studies of breast cancer with efficient MRS methods.

Proper citation: Richard M. Lucas Center for Imaging (RRID:SCR_001406) Copy   

•   Source: SciCrunch Registry
  

http://www.utsouthwestern.edu/education/medical-school/departments/airc/southwestern-nmr-center/index.html

Biomedical technology research center that develops and applies new methods for analysis of metabolic networks in intact tissues, animals and human patients. The importance of understanding abnormal metabolism in common diseases such as cancer, diabetes and heart disease has long been appreciated. Because of constraints in technology, however, much of this research has been conducted in isolated systems where clinical relevance may be uncertain. Progress in magnetic resonance technology provides a foundation for major advances towards new ways of imaging metabolism in patients. These new techniques offer the advantage of imaging biochemical pathways without radiation. The focus of this Resource is to bring these technologies to a level where clinical research is feasible through the development of new MR contrast agents, NMR spectroscopy at high fields, and imaging of hyperpolarized 13C.

Proper citation: Southwestern NMR Center for In Vivo Metabolism (RRID:SCR_001429) Copy   

•   Source: SciCrunch Registry
  

http://bmsr.usc.edu/

Biomedical technology resource center dedicated to the advancement of the state-of-the-art in biomedical modeling and simulation through Core and Collaborative Research projects, as well as the dissemination of this knowledge and related software through Service, Training and Dissemination activities aimed at the biomedical community at large. The BMSR includes four core research projects: * Pharmacokinetic/Pharmacodynamic Systems Analysis * Nonlinear Modeling of Complex Biomedical Systems * Modeling of Autonomic, Metabolic and Vascular Control Interactions * Nonlinear Modeling of the Hippocampus Fifteen Collaborative Research Projects serve as challenging test grounds for the Resource's methodologies and expertise.

Proper citation: Biomedical Simulations Resource (RRID:SCR_001952) Copy   

•   Source: SciCrunch Registry
  

http://ranchobiosciences.com/gse27831/

Curated data set from gene expression profiles of 29 unique samples from uveal melanoma patients that were measured on Affymetrix microarray. In addition, expression of syntenin-1 was measured by RT-PCR and this data is also available in the study.

Proper citation: GSE27831 (RRID:SCR_003646) Copy   

•   Source: SciCrunch Registry
  

http://ranchobiosciences.com/gse20194/

Curated data set of gene expression data from 230 stage I-III breast cancers that were generated from fine needle aspiration specimens of newly diagnosed breast cancers before any therapy. The biopsy specimens were collected sequentially during a prospective pharmacogenomic marker discovery study between 2000 and 2008. These specimens represent 70-90% pure neoplastic cells with minimal stromal contamination. In the study, patients received 6 months of preoperative (neoadjuvant) chemotherapy including paclitaxel, 5-fluorouracil, cyclophosphamide and doxorubicin followed by surgical resection of the cancer.

Proper citation: GSE20194 (RRID:SCR_003645) Copy   

•   Source: SciCrunch Registry
  

http://ranchobiosciences.com/gse4698/

Curated data set where gene expression profiling was performed on 60 prospectively collected samples of children with first relapse of acute lymphoblastic leukemia enrolled on the relapse trial ALL-REZ BFM 2002 of the Berlin-Frankfurt-Muenster study group.

Proper citation: GSE4698 (RRID:SCR_003644) Copy   

•   Source: SciCrunch Registry
  

http://ranchobiosciences.com/gse4271/

Curated data set from a study that investigated 77 primary high-grade astrocytomas and 23 matched recurrences so that changes in gene expression related to both survival and disease progression can be identified. Samples in the study include WHO grade III and IV astrocytomas with a wide range of survival times.

Proper citation: GSE4271 (RRID:SCR_003643) Copy   

•   Source: SciCrunch Registry
  

https://grail.com/clinical-studies/ccga-study/

Prospective, observational, longitudinal, study designed to characterize landscape of genomic cancer signals in blood of people with and without cancer. Sudy includes people in the USA and Canada who had cancer at the time of enrollment, newly diagnosed, and not yet received treatment, and people who did not have known cancer diagnosis.

Proper citation: Circulating Cell-free Genome Atlas project (RRID:SCR_023878) Copy   

•   Source: SciCrunch Registry
  

https://seer.cancer.gov/statfacts/

Collection of statistical summaries for number of common cancer types. They were developed to provide quick overview of frequently requested cancer statistics. Available statistics may include incidence, mortality, survival, stage, prevalence, and lifetime risk. Links to additional resources from NCI including risk factors, treatment, and clinical trials are also provided. The statistics will be updated annually to coincide with the SEER data release.

Proper citation: National Cancer Institute Cancer Statistics Cancer Stat Facts (RRID:SCR_024437) Copy   

•   Source: SciCrunch Registry
  

https://seer.cancer.gov/siterecode/icdo3_dwhoheme/index.html

Website describing International Classification of Diseases-Oncology codes that corresponds to different cancer sites in the Surveillance, Epidemiology, and End Results (SEER) registry.

Proper citation: NCI Site Recode ICD-O-3/WHO 2008 Definition (RRID:SCR_024687) Copy   

•   Source: SciCrunch Registry
  

http://www.medinadiscovery.com/

A non-profit research center established through a public-private alliance between the Regional government of Andalusia, the pharmaceutical company Merck Sharp & Dohme Spain S.A. (MSD), and the University of Granada, that is focused on: # Discovery of new compounds and therapies as new leads for drug development # Contract Research Services: High throughput screening services for lead discovery, ADME/TOX, bioanalysis and metabolomics MEDINA offers 1) natural products screening services for lead discovery on therapeutic targets developed by the customers and 2) compound profiling services for their drug candidates, using a counterscreening panel designed to determine potential risks in cardiovascular safety and drug-drug interactions.

Proper citation: MEDINA Foundation (RRID:SCR_004079) Copy   

•   Source: SciCrunch Registry