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https://abctb.org.au/abctbNew2/default.aspx

A tissue bank which houses and supplies cancerous tissue for use by the research community. Along with tissue, the bank collects clinical history, lifestyle factors, breast pathology, treatment information, and follow up information.

Proper citation: Australia Breast Cancer Tissue Bank (RRID:SCR_000926) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

•   Source: SciCrunch Registry

http://www.roswellpark.edu/shared-resources/data-bank-and-biorepository

Collects and provides de-identified biospecimens and associated epidemiological and clinical data to meet the scientific needs of investigators. Newly diagnosed patients are asked to contribute data and specimens to the DBBR prior to treatment. Other patients with who have benign disease or advanced disease and have undergone treatment are also enrolled based on anticipated use of data and samples for research. Additionally, non-patients (family members and friends of patients and community members) with no personal history of cancer are asked to participate in the biorepository as controls. Specimens and data are procured with protected health information (PHI) and de-identified prior to distribution to investigators with hypothesis driven IRB reviewed studies. An extensive data collection and management system is in place to track informed consent, questionnaire collection and follow up, epidemiological questionnaire data, clinical data, biospecimens and their derivatives. Research Services * Availability of a bank of prospectively collected blood specimens (serum, plasma, buffy coat, red blood cells and DNA) from cancer patients, high risk individuals and healthy controls for research. * Collection, linking and distribution of epidemiologic and clinical data with biospecimens. * Study-specific biospecimen and data procurement to meet the needs of individual studies, including: ** Participant identification, eligibility screening and informed consent ** Serial biospecimen procurement prior to and throughout treatment ** Study specific collection of biospecimens other than blood (buccal cells, sputum, and urine) ** Procurement and distribution of fresh biospecimens ** Collection of extended clinical and risk factor data

Proper citation: Roswell Park Data Bank and BioRepository (RRID:SCR_003607) Copy   

•   Source: SciCrunch Registry

https://www.signalingpathways.org/ominer/query.jsf

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on February 25, 2022.Software tool as knowledge environment resource that accrues, develops, and communicates information that advances understanding of structure, function, and role in disease of nuclear receptors (NRs) and coregulators. It specifically seeks to elucidate roles played by NRs and coregulators in metabolism and development of metabolic disorders. Includes large validated data sets, access to reagents, new findings, library of annotated prior publications in field, and journal covering reviews and techniques.As of March 20, 2020, NURSA is succeeded by the Signaling Pathways Project (SPP).

Proper citation: Nuclear Receptor Signaling Atlas (RRID:SCR_003287) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~spike/

Database of curated human signaling pathways with an associated interactive software tool for analysis and dynamic visualization of pathways. Individual pathway maps can be viewed and downloaded; the entire database may be browsed, or launched via a map viewer tool that allows dynamic visualization of the database and save networks in XGMML format that can be viewed in all generic XGMML viewers. Map Topics * Cell cycle progress and check points * DNA damage response * Programmed cell death related processes * Stress-activated transcription factors * Mitogen-activated protein kinase pathways * Immune response signaling * HEarSpike: hearing related pathways

Proper citation: SPIKE (RRID:SCR_010466) Copy   

•   Source: SciCrunch Registry

http://data-analysis.charite.de/care/

Comprehensive database of cancer relevant proteins and compound interactions supported by experimental knowledge.Knowledgebase for drug-target relationships related to cancer as well as for supporting information or experimental data.

Proper citation: CancerResource (RRID:SCR_011945) Copy   

•   Source: SciCrunch Registry

https://genome-cancer.ucsc.edu/

A suite of web-based tools to visualize, integrate and analyze cancer genomics and its associated clinical data. It is possible to display your own clinical data within one of their datasets.

Proper citation: UCSC Cancer Genomics Browser (RRID:SCR_011796) Copy   

•   Source: SciCrunch Registry

http://www.cancerrxgene.org/

A genomics database project is an academic research program to identify molecular features of cancers that predict response to anti-cancer drugs.

Proper citation: Genomics of Drug Sensitivity in Cancer (RRID:SCR_011956) Copy   

•   Source: SciCrunch Registry

http://cbbiweb.uthscsa.edu/KMethylomes/

Datbase and web-based system for visualization and analysis of genome-wide methylation data of human cancers.

Proper citation: Cancer Methylome System (RRID:SCR_012013) Copy   

•   Source: SciCrunch Registry

http://dbcat.cgm.ntu.edu.tw/

A database of CpG islands and analytical tools for identifying comprehensive methylation profiles in cancer cells.

Proper citation: DBCAT (RRID:SCR_012014) Copy   

•   Source: SciCrunch Registry

http://www.cravat.us/

A web-based application designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis.

Proper citation: CRAVAT (RRID:SCR_012776) Copy   

•   Source: SciCrunch Registry

https://rtips.cancer.gov/rtips/index.do

Database of cancer control interventions and program materials. It is designed to provide program planners and public health practitioners easy and immediate access to research-tested materials.

Proper citation: Research-tested Intervention Programs (RTIPs) (RRID:SCR_016042) 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://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

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://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

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

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://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

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