Tools   Select Another Resource Report Type

http://www.einstein.yu.edu/centers/ictr/

Patient-derived specimens are essential to research in genomics, proteomics, and biomarkers. We provide banking for biological fluid and tissue specimens as well as human DNA and RNA. We provide secure archival sample storage as well as clinically-annotated specimen biobanks for defined research projects. The core serves the human research blood and tissue banking needs of clinical and translational researchers. Samples can be banked by an individual PI or by a consortium of investigators. All samples are tracked and archived using a secure tracking database, the Einstein-Montefiore Bio-Repository Databank (EM-BRED), http://informatics30.aecom.yu.edu/em-bred/default.aspx. EM-BRED provides qualified investigators with a solution to securely link patient specimens to clinical and pathological data. It consists of a user-friendly query engine that allows for comprehensive specimen search, and ultimately to build clinical annotations of relevance. The facility works under the best practices set out by NCI and ISBER (2006) for collection, storage, and retrieval of human biological materials for research.

Proper citation: Einstein-Montefiore Institute for Clinical and Translational Research Biorepository (RRID:SCR_005297) Copy   

•   Source: SciCrunch Registry

http://cancer.osu.edu/research/cancerresearch/sharedresources/ltb/Pages/index.aspx

The OSU Comprehensive Cancer Center Leukemia Tissue Bank Shared Resource (LTBSR) facilitates the successful translation of basic leukemia research to the clinical setting via an extensive repository of tissue samples and accompanying pathologic, cytogenetic and clinical data for ready correlation of clinical and biological results. The LTBSR, which is an NCI-sponsored biorepository, has more than 40,000 vials of cryopreserved viable cells and 13,000 vials of matched frozen plasma and/or serum samples from more than 4,000 patients treated for leukemia and other malignancies. Committed to furthering translational research efforts for OSUCCC - James members and the cancer research community, the LTBSR provides investigators with training and technical support as well as procurement, processing, storage, retrieval and distribution of clinical research materials. In many cases, the LTBSR serves as the central processing lab for multi-site trials in which the principal investigator is an OSUCCC - James member. The LTBSR's goals are to: * Provide a central collection, processing and a state-of-the-art repository for samples collected from leukemia patients treated on OSUCCC - James protocols, and * Provide materials to investigators involved in collaborative studies with OSU, who examine relevant cellular and molecular properties of leukemia and correlate these properties with clinical or population-based outcomes.

Proper citation: Ohio State Leukemia Tissue Bank (RRID:SCR_000529) Copy   

•   Source: SciCrunch Registry

http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy   

•   Source: SciCrunch Registry

http://pstiing.icr.ac.uk/

A publicly accessible knowledgebase about protein-protein, protein-lipid, protein-small molecules, ligand-receptor interactions, receptor-cell type information, transcriptional regulatory and signal transduction modules relevant to inflammation, cell migration and tumourigenesis. It integrates in-house curated information from the literature, biochemical experiments, functional assays and in vivo studies, with publicly available information from multiple and diverse sources across human, rat, mouse, fly, worm and yeast. The knowledgebase allowing users to search and to dynamically generate visual representations of protein-protein interactions and transcriptional regulatory networks. Signalling and transcriptional modules can also be displayed singly or in combination. This allow users to identify important "cross-talks" between signalling modules via connections with key components or "hubs". The knowledgebase will facilitate a "systems-wide" understanding across many protein, signalling and transcriptional regulatory networks triggered by multiple environmental cues, and also serve as a platform for future efforts to computationally and mathematically model the system behavior of inflammatory processes and tumourigenesis.

Proper citation: pSTIING (RRID:SCR_002045) Copy   

•   Source: SciCrunch Registry

http://magi.cs.brown.edu/

A tool for annotating, exploring, and analyzing gene sets that may be associated with cancer.

Proper citation: Mutation Annotation and Genomic Interpretation (RRID:SCR_002800) 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://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://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

http://web.mit.edu/spectroscopy/facilities/lbrc.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Biomedical technology research center that develops basic scientific understanding and new techniques required for advancing clinical applications of lasers and spectroscopy. LBRC merges optical spectroscopy, imaging, scattering, and interferometry techniques to study biophysics and biochemistry of healthy and diseased biological structures from subcellular to entire-organ scale.

Proper citation: Laser Biomedical Research Center (RRID:SCR_000106) Copy   

•   Source: SciCrunch Registry

http://www.civm.duhs.duke.edu/

Biomedical technology research center dedicated to the development of novel imaging methods for the basic scientist and the application of the methods to important biomedical questions. The CIVM has played a major role in the development of magnetic resonance microscopy with specialized MR imaging systems capable of imaging at more than 500,000x higher resolution than is common in the clinical domain. The CIVM was the first to demonstrate MR images using hyperpolarized 3He which has been moved from mouse to man with recent clinical trials performed at Duke in collaboration with GE. More recently the CIVM has developed the molecular imaging workbench---a system dedicated to multimodality cardiopulmonary imaging in the rodent. Their collaborators are employing these unique imaging systems in an extraordinary range of mouse and rat models of neurologic disease, cardiopulmonary disease and cancer to illuminate the underlying biology and explore new therapies.

Proper citation: Center for In Vivo Microscopy (RRID:SCR_001426) Copy   

•   Source: SciCrunch Registry

https://github.com/Illumina/strelka/

Software for somatic single nucleotide variant (SNV) and small indel detection from sequencing data of matched tumor-normal samples. Strelka2 germline and somatic small variant caller.

Proper citation: Strelka2 (RRID:SCR_005109) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse4922/

Curated data set of a study that investigated the expression profiles of 347 primary invasive breast tumors on Affymetrix microarrays. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed in GSE4922. The Stockholm cohort data can be accessed at GEO Series GSE1456.

Proper citation: GSE4922 (RRID:SCR_003557) Copy   

•   Source: SciCrunch Registry

http://www.yale.edu/herzongroup/Herzon_Lab/Home.html

My laboratory has created a family of natural product-inspired anticancer agents. We have evaluated our compounds at the Yale Center for Chemical Genomics, and they are exhibiting IC50 values in the low nM range against K562, HeLa, LnCAP, and HCT-116 lines. Their mechanism of action is unknown, although the natural products have been shown to cleave DNA. An evaluation of the natural products at the NCI has shown that they have a toxicity profile that is distinct from other known DNA damaging agents. We can readily access gram-quantities of these agents for further studies. We are looking for researchers who might find these compounds useful in medicinal applications, for example, for treatment of a specific cancer. We are capable of synthesizing new analogs, such as those incorporating a specific recognition or targeting element, and would be excited to pursue this avenue of research.

Proper citation: Herzon Lab (RRID:SCR_008850) Copy   

•   Source: SciCrunch Registry

https://wonder.cdc.gov/cancer.html

United States Cancer Statistics public information data provided by Centers for Disease Control and Prevention.

Proper citation: United States Cancer Statistics Public Information Data (RRID:SCR_024896) Copy   

•   Source: SciCrunch Registry

http://sharedresources.fredhutch.org/core-facilities/scientific-imaging

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Scientific imaging service that serves as a centralized facility for imaging and visualization. The core facility provides access to time lapse and 3-D microscopy and quantitative autoradiography.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Scientific Imaging (RRID:SCR_015340) Copy   

•   Source: SciCrunch Registry

http://sharedresources.fredhutch.org/core-facilities/comparative-medicine

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Core facility that provides a variety of animal housing, veterinary and research support services.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Comparative Medicine (RRID:SCR_015326) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Core facility that provides expertise and support for generating genomics-based data. Services for DNA arrays, genetic analysis, and high-throughput screening are provided through three specialized laboratories.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Genomics Shared Resource (RRID:SCR_015327) Copy   

•   Source: SciCrunch Registry

http://firebrowse.org/

Portal provides access to cancer genomic data from variety of analyses: clinical, copy number, miR, miRseq, mRNA, mRNAseq, mutation and pathway analyses. Provides comprehensive suite of interdependent analyses of those data, including: correlations, clustering, and GISTIC and MutSigCV. Companion portal to the Broad Institute GDAC Firehose analysis pipeline, and was developed to cull and analyze data generated by The Cancer Genome Atlas (TCGA), which characterizes and identifies genomic patterns in human cancer models.

Proper citation: FireBrowse (RRID:SCR_026320) Copy   

•   Source: SciCrunch Registry