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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

http://clinicalinformatics.stanford.edu/services/biobank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 7th, 2023. An online, searchable record of biospecimen attributes and storage location for the following three biobanks at Stanford: * The Bone Marrow Transplant (BMT) program * The Hematology biospecimen bank is a research sample repository focusing on blood, plasma and bone marrow, primarily from leukemia patients. * Cancer Center Pathology Core: The Stanford Comprehensive Cancer Center Tissue Bank stores research samples of both solid tumor and blood from cancer patients, with an emphasis on prostate. As of November 2009, the system contains data on 50,000 biospecimens stored in multiple banks at Stanford. An anonymous Biospecimen Locator allows Stanford researchers to search the STRIDE Virtual Biospecimen Bank for suitable samples without having to know, or expose, any protected patient-specific information. Having determined that suitable specimens exist in one of the constituent biospecimens banks, the researcher can generate a Web-based request form to obtain additional information from the appropriate bank operator(s). Access to specimens is restricted to Stanford Faculty and Staff or affiliates., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: STRIDE Virtual Biospecimen Bank (RRID:SCR_008667) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

•   Source: SciCrunch Registry

http://methycancer.psych.ac.cn/

Database to study interplay of DNA methylation, gene expression and cancer that hosts both highly integrated data of DNA methylation, cancer-related gene, mutation and cancer information from public resources, and the CpG Island (CGI) clones derived from our large-scale sequencing. Interconnections between different data types were analyzed and presented. Search tool and graphical MethyView are developed to help users access all the data and data connections and view DNA methylation in context of genomics and genetics data. The search tool and graphical MethyView are developed to help users access all the data and data connections and view DNA methylation in context of genomics and genetics data. As part of the Cancer Epigenomics Project in China, MethyCancer serves as a platform for sharing data and analytical results from the Cancer Genome/Epigenome Project in China with colleagues all over the world.

Proper citation: MethyCancer (RRID:SCR_013399) Copy   

•   Source: SciCrunch Registry

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://portal.gdc.cancer.gov/

A unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.

Proper citation: Genomic Data Commons Data Portal (GDC Data Portal) (RRID:SCR_014514) 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://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://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://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://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

http://www.stanford.edu/~rnusse/pathways/targets.html

A list of target genes of Wnt/beta-catenin signaling. Suggestions for additions are welcome. Direct targets are defined as those with Tcf binding sites and demonstrating that these sites are important.

Proper citation: Target genes of Wnt/beta-catenin signaling (RRID:SCR_007022) Copy   

•   Source: SciCrunch Registry

http://www.biobanks.se/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 6th, 2022. The biobank comprises paraffin blocks of surgical and autopsy tissue samples and corresponding histological slides as well as cytological material consisting of slides of vaginal smears, fine needle aspiration biopsies and exfoliative cytological material. The tissue samples date back until 1944 and most of the cytological samples until 1970. A subunit of the bank constitutes the National Tissue Microarray Centre. This center is supported by SWEGENE with the purpose to organize and construct tissue microarrays (TMA:s) for high throughput molecular pathology research on various kinds of tumors and other diseases. By linking the TMA.s to long-term and complete clinical follow-up data, prognostic and predictive studies will be facilitated. Biobank content: * Approximately 2,4 million paraffin blocks of surgical tissue specimens, * 1,1 million paraffin blocks of tissue samples from autopsies, * 3,8 million histological slides and * 1,6 million cytology slides. At present, the Tissue Microarray Centre includes: * A consecutive series of all invasive breast cancers (n=600) diagnosed in Malmo between 1988 and 1992. * All incident breast cancers within the Malmo Diet and Cancer cohort (n=400). * A subgroup of 600 pre-menopausal primary breast cancers within the nationwide, population-based randomized tamoxifen trial SBII:2. * 180 primary breast cancers from post-menopausal women included in a similar study. * A set of 120 extremely well characterized primary breast cancer samples with a clinical follow-up of 10 years. More than 40 relevant tumor biological parameters have been recorded in this material and it is therefore useful for a first screening of a marker in order to identify associations to other gene products. * 350 renal cell carcinomas (In collaboration with NUS). We provide researchers with state-of-the-art population based tissue microarrays with long-term and complete follow-up data on survival and treatment. With the TMA-technology, valuable biobank material will be preserved, allowing high throughput in-situ analyses of various tumors and other diseases with a minimal waste of tissue.

Proper citation: UMAS University Hospital - Biobanks of the Department of Clinical Pathology and Cytology (RRID:SCR_005957) Copy   

•   Source: SciCrunch Registry

http://www.kreftregisteret.no/en/Research/Janus-Serum-Bank/

The Janus Serum Bank has blood samles from 317 000 Norwegians. The biobank is reserved for cancer research, and is internationally unique regarding size and number of cancer cases. The Janus Serum Bank is a population based biobank reserved for cancer research. The specimens are collected during the period from 1972-2004 and are stored at 25 degrees Celsius. The samples originate from 317 000 persons in Norway who have participated in health studies and also from blood donors in and around Oslo. Today, samples are only collected from earlier donors in the Janus Serum Bank who have developed cancer. The Bank is internationally unique regarding size and number of cancer cases. Annual linkage to the Cancer Registry shows that 52 500 donors are diagnosed with cancer as of December 31, 2009. The main goals of the biobank are to make the material available to cancer researchers over the whole world and deliver quality assured samples and data. The Janus Serum Bank is registered in the Biobank Register (Notification number 737)

Proper citation: Janus Serum Bank (RRID:SCR_005885) Copy   

•   Source: SciCrunch Registry

http://www.cancerbiobank.org/

CCPRB (Cancer Control using Population-based Registries and Biobanks) is a Network of Excellence project within the sixth framework programme of the European Union. It is aiming at improved control of cancer by facilitating research linking biobanks and cancer registries. The project involves a systematic quality assurance and continuous development of standards and norms for human sample biobanks in Europe, as well as development of improved integrity-protection standards in the handling of sensitive information in connection with biobank-based research. The samples in the biobanks will be used in large-scale cancer research searching for genetic and infectious causes to cancer, in particular in the areas of breast and colorectal cancer and childhood leukemia. Project objectives: * Provide the study base for uniquely large population-based prospective studies on cancer * Define and implement a generally applicable European Quality Standard for Biobanking that will include improved data and specimen standardization, acquisition and analysis, reliable and standardized statistical analysis as well as improved management and co-ordination of European biobanks. * Define and promote the implementation of integrity-proof methods for biobank-based research involving well defined and secure third party code-keeping systems. * Enable large-scale, population-based research on: ** evaluation of cancer treatment and role of molecular markers in treatment selection ** use over-generation registry linkages applied to large biobank cohorts to identify and evaluate genetic predisposition associated with increased cancer risk as well as interactions with common environmental exposures. ** use over-generation registry linkages applied to large biobank cohorts to explore and evaluate intrauterine exposures associated with increased cancer risk ** exploit the power of large population cohorts for design of optimal strategies for cancer prevention and its evaluation. * Establish a Europe-wide network for spreading the awareness of i) the data, samples and knowledge generated European biobank-based research ii) possibilities for future biobank-based research and iii) the best practice quality standards for biobank-based research.

Proper citation: Cancer Control using Population-based Registries and Biobanks (RRID:SCR_004902) Copy   

•   Source: SciCrunch Registry

http://www.dna-network.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 6, 2011. A project to collect, store and study DNA samples from tens of thousands of healthy volunteers and patients with diseases of major public importance. It aims to identify genes that are risk factors for the conditions. The network consists of 13 collections led by different clinicians throughout the UK. At its heart is an archive infrastructure which manages the DNA and the information associated with it. The European Collection of Cell Cultures in Porton Down handles the blood, peripheral blood lymphocytes and EBV-transformed cell lines, while the Centre for Integrated Genomic Medical Research at Manchester University manages the DNA. These banked samples are available to UK and international researchers, who can examine data and set up collaborative work by registering at the DNA Network's website. The conditions for which samples are currently collected and stored are: Acute leukemia, Asthma and eczema, Late onset Alzheimer's disease, Breast cancer, Colorectal cancer, Coronary artery disease, Glomerulonephritis, Hypertension, Age-related macular degeneration, Multiple sclerosis, Parkinson's disease, Type 2 diabetes, Unipolar depression.

Proper citation: UK DNA Banking Network (RRID:SCR_010619) Copy   

•   Source: SciCrunch Registry