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https://pdc.cancer.gov/pdc/

Portal to make cancer related proteomic datasets easily accessible to public. Facilitates multiomic integration in support of precision medicine through interoperability with other resources. Developed to advance our understanding of how proteins help to shape risk, diagnosis, development, progression, and treatment of cancer. One of several repositories within NCI Cancer Research Data Commons which enables researchers to link proteomic data with other data sets (e.g., genomic and imaging data) and to submit, collect, analyze, store, and share data throughout cancer data ecosystem. PDC provides access to highly curated and standardized biospecimen, clinical, and proteomic data, intuitive interface to filter, query, search, visualize and download data and metadata. Provides common data harmonization pipeline to uniformly analyze all PDC data and provides advanced visualization of quantitative information. Cloud based (Amazon Web Services) infrastructure facilitates interoperability with AWS based data analysis tools and platforms natively. Application programming interface (API) provides cloud-agnostic data access and allows third parties to extend functionality beyond PDC. Structured workspace that serves as private user data store and also data submission portal. Distributes controlled access data, such as patient-specific protein fasta sequence databases, with dbGaP authorization and eRA Commons authentication.

Proper citation: Proteomic Data Commons (RRID:SCR_018273) Copy   

•   Source: SciCrunch Registry

https://portal.imaging.datacommons.cancer.gov

Portal for finding and analyzing cancer imaging data. Part of Cancer Research Data Commons to support cancer imaging research. Provides cloud based access to medical imaging data and library of analytical tools and workflows to share, analyze, and visualize multi modal imaging data from both clinical and basic cancer research studies.

Proper citation: NCI Imaging Data Commons (RRID:SCR_019127) Copy   

•   Source: SciCrunch Registry

https://datacommons.cancer.gov

Cloud based data science infrastructure that provides secure access to cancer research data from NCI programs and key external cancer programs. Serves as coordinated resource for public data sharing of NCI funded programs. Users can explore and use analytical and visualization tools for data analysis. Enables to search and aggregate data across repositories including Cancer Data Service, Clinical Trial Data Commons, Genomic Data Commons, Imaging Data Commons, Integrated Canine Data Commons, Proteomic Data Commons.

Proper citation: Cancer Research Data Commons (RRID:SCR_019128) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://pubs.rsc.org/en/content/articlehtml/2017/LC/C7LC00703E

Equipment that is a magnetic micropore chip for rapid unbiased circulating tumor cell isolation and in situ RNA analysis. The chip detects tumor cells and can help doctors treat patients with these tumors.

Proper citation: CaTCh FISH Chip (RRID:SCR_015810) Copy   

•   Source: SciCrunch Registry

http://www.lincsproject.org/

Project to create network based understanding of biology by cataloging changes in gene expression and other cellular processes when cells are exposed to genetic and environmental stressors. Program to develop therapies that might restore pathways and networks to their normal states. Has LINCS Data Coordination and Integration Center and six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.

Proper citation: LINCS Project (RRID:SCR_016486) Copy   

•   Source: SciCrunch Registry

http://ccmi.org

Initiative to enable cancer discovery and treatment based on complete elucidation of molecular networks underlying cancer. CCMI leverages advanced interaction mapping and computational facilities to generate and analyze cancer networks.

Proper citation: Cancer Cell Map Initiative (RRID:SCR_023043) Copy   

•   Source: SciCrunch Registry

http://cahub.cancer.gov/about/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. A national center for biospecimen science and standards to advance cancer research and treatment. It was created in response to the critical and growing need for high-quality, well-documented biospecimens for cancer research. The initiative builds on resources already developed by the NCI, including the Biospecimen Research Network and the NCI Best Practices for Biospecimen Resources, both of which were developed to address challenges around standardization of the collection and dissemination of quality biospecimens. caHUB will develop the infrastructure for collaborative biospecimen research and the production of evidence-based biospecimen standard operating procedures.

Proper citation: caHUB (RRID:SCR_009657) Copy   

•   Source: SciCrunch Registry

http://www.hemonc.org

Medical wiki of interventions, regimens, and general information relevant to fields of hematology and oncology. Knowledge base for hematology and oncology providers, containing details about hematology/oncology drugs and treatment regimens. Any healthcare professional can sign up to contribute. Acuracy and completeness of content is overseen by Editorial Board.

Proper citation: HemOnc Knowledgebase (RRID:SCR_023436) Copy   

•   Source: SciCrunch Registry

https://www.cnio.es/ing/

A cancer research center whose goal is to offer innovative technoligies to spur the develpment of new methods of diagnosing and treating cancer. CNIO contains a variety of programs of investigation, including a biotechnology program, a clinical research program, and a molecular oncology program. CNIO also provides services that allow researchers to access and use technologies and tools such as cytogenetics and monoclonal antibodies, and hosts a biomedical biobank.

Proper citation: Spanish National Cancer Research Center (RRID:SCR_014054) 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.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

http://www.istge.it/crb/english.htm

The Centro di Risorse Biologiche (CRB-IST), institutional facility of IST, has been recently established by the General Director (Deliberation number 624 July 11, 2008). It aims at co-ordinating already existing biobanking activities, and participating in the European Infrastructure of Biobanks and Biomolecular Resources (BBMRI), in preparation in the frame of the 7th FP of the European Community. Aims: * to facilitate high quality translational research dependent on biological material and data * to address ethical issues on biobanking * to promote the project at the population level * to co-ordinate the IST biobanks and cell banks * to harmonize technical and management SOPs, according to international best practices * to help reduce costs for collection and storage of biological material * to favor institutional recognition at a regional, national and international level - to sustain the role of the Institute in the European infrastructure.

Proper citation: Biological Resource Centre - National Institute for Cancer Research (RRID:SCR_010548) 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