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http://biobankireland.com/

Biobank Ireland Trust promotes the development of an Irish Hospital Biobank Network to coordinate collection of small samples of cancer and normal tissue and coded patient data from those having a cancer operation. This will facilitate international molecular research collaborations, which may help identify the best treatment for each individual patient - personalized medicine. Biobank Ireland is promoting the development of a Hospital Biobank Network throughout the island of Ireland as a bridge between cancer research and care. This new infrastructure will facilitate large national and international translational research collaborations that will raise Ireland''s research profile and benefit those with cancer. Researchers will have online access to samples and to restricted patient data from participating hospitals and an equitable withdrawal process for scientifically and ethically approved projects. Important research results will be explained to the public. Other Objectives: * To facilitate (inter)national translational research collaborations that may lead to new tests and better, less toxic treatments for those with cancer * To enable molecular research on cancer tissue from clinical trials patients identify the best treatment for each individual patient ������??personalized medicine������?? * Researchers will have online access to samples and restricted patient data from participating hospitals, and a fair release process for scientifically and ethically approved projects * Biobank Ireland recognizes the need to have harmonization in biobanking around the world * Important research results will be explained to the public * Biobank Ireland will seek to have the hospital-based Biobank Network funded by government as standard of care

Proper citation: Biobank Ireland Trust (RRID:SCR_006430) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Core provides bioinformatics specialists available to assist researchers with processing, exploring, and understanding genomics data.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Bioinformatics Resource (RRID:SCR_015324) 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

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://www.azcc.arizona.edu/research/shared-services/tacmass/tissue-acquisition

TACMASS collects, preserves, and banks biospecimens obtained from Arizona Cancer Center surgical patients who are seen by University Medical Center surgeons and oncologists. Biospecimens collected at the time of surgery include fresh surgical tissue, blood and urine. Serum, plasma and genomic DNA are harvested from the whole blood. AZCC Members and collaborators may request the use of banked biospecimens through TACMASS. The patient's surgeon or oncologist is responsible for consenting the patient for submission of surgical specimens to the AZCC BioRepository (IRB #06-0609-04, Setsuko Chambers, PI). The surgeon and the Department of Pathology attending physicians and residents are responsible for identifying appropriate tissue for banking that will not compromise pathological diagnosis. Tumor and/or normal adjacent tissue, identified by gross examination, that will not be needed for pathological diagnosis are preserved by fixing in formalin, snap freezing, and/or fixing in RNALater. Histological diagnosis is rendered on each piece of formalin-fixed and snap frozen tissue by Hematoxylin and Eosin staining (H&E). Everyone involved in submitting specimens to the Tumor Bank must maintain a current CITI Certification.

Proper citation: Arizona Cancer Center Tumor Bank (RRID:SCR_003544) Copy   

•   Source: SciCrunch Registry

http://www.netpath.org/

A manually curated resource of signal transduction pathways in humans. All pathways are freely available for download in BioPAX level 3.0, PSI-MI version 2.5 and SBML version 2.1 formats. The slim pathway models representing only core reactions in each pathway are available at NetSlim. All the NetPath pathway models are also submitted to WikiPathways., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NetPath (RRID:SCR_003567) Copy   

•   Source: SciCrunch Registry

http://www.ariad.com/

Cambridge, Massachusetts-based biotechnology company focused on cancer. Focus areas are blood cancers and solid tumors. Compounds: ponatinib, AP26113, ridaforolimus and AP1903., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ARIAD (RRID:SCR_008559) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

•   Source: SciCrunch Registry

https://www.cancer.gov/about-cancer/treatment/drugs

Portal to find consumer friendly information about drugs for cancer and conditions related to cancer. The list is in alphabetical order by generic name and brand name.

Proper citation: NIH NCI list of FDA approved cancer drugs (RRID:SCR_021841) Copy   

•   Source: SciCrunch Registry

http://seer.cancer.gov/resources/

Portal provides SEER research data and software SEER*Stat and SEER*Prep. SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas can be used to examine stage at diagnosis by race/ethnicity, calculate survival by stage at diagnosis, age at diagnosis, and tumor grade or size, determine trends and incidence rates for various cancer sites over time. SEER releases new research data every Spring based on the previous November’s submission of data.

Proper citation: SEER Datasets and Software (RRID:SCR_003293) Copy   

•   Source: SciCrunch Registry

http://gepia.cancer-pku.cn

Web server for cancer and normal gene expression profiling and interactive analyses. Interactive web server for analyzing RNA sequencing expression data of tumors and normal samples from TCGA and GTEx projects, using standard processing pipeline. Provides customizable functions such as tumor or normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.

Proper citation: Gene Expression Profiling Interactive Analysis (RRID:SCR_018294) Copy   

•   Source: SciCrunch Registry

http://www.ngfn.de/en/start.html

The program of medical genome research is a large-scale biomedical research project which extends the national genome research net (NGFN) and will be funded by the federal ministry of education and research (BMBF) from 2008-2013. Currently the program includes two fields: * Research ** NGFN-Plus: With the aim on combating diseases that are central to health policy, several hundred researchers are systematically investigating the complex molecular interactions of the human body. They are organized in 26 Integrated Genome Research Networks. * Application ** NGFN-Transfer: The rapid transfer of results from medical genome research into medical and industrial application is the aim of the scientists from research institutes and biomedical enterprises that cooperate in eight Innovation Alliances. AREAS OF DISEASE * Cardiovascular disease * Cancer * Neuronal diseases * Infections and Inflammations * Environmental factors

Proper citation: National Genome Research Network (RRID:SCR_006626) Copy   

•   Source: SciCrunch Registry

https://dctd.cancer.gov/programs/cdp/organization/bbrb

BBRB supports medical discovery and precision medicine by providing leadership, tools, and resources to the biobanking community. Provides input on policy related to biobanking and supports the availability of biospecimens for research. Develops standardized procedures for biospecimen science and research; conducts and sponsors research on the effects of biospecimen preanalytical factors; leads and supports major scientific initiatives requiring high-quality biospecimens; and supports investigations into the ethical, legal, and social issues concerning biospecimen collection and use.

Proper citation: Biorepositories and Biospecimens Research Branch (RRID:SCR_013979) Copy   

•   Source: SciCrunch Registry

http://sharedresources.fredhutch.org/core-facilities/cceh-administration

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July,27,2022. Core facility that provides scientific and budgetary oversight for all CCEH activities. This includes training programs, high school summer internships, and and pilot and feasibility program for new projects.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology (RRID:SCR_015320) Copy   

•   Source: SciCrunch Registry

http://www.lji.org/faculty-research/scientific-cores/functional-genomics-sequencing-core/#overview

Non profit collaborative research organization located in La Jolla, California, UCSD Research Park. Institute researches immunology and immune system diseases to pinpoint specific genes involved, accelerate progress toward development of new treatments and vaccines to prevent and cure type 1 diabetes, cancer and infectious disease. Developer of Immune Epitope Database (IEDB). Provides core facilities with access to equipment, technologies, training and expertise to support innovative research.

Proper citation: La Jolla Institute for Immunology (RRID:SCR_014837) Copy   

•   Source: SciCrunch Registry

https://ccsp.hms.harvard.edu/

Center includes studies for responsiveness and resistance to anti cancer drugs. Committed to training students and postdocs, promoting junior faculty and ensuring that data and software are reproducible, reliable and publicly accessible. Member of National Cancer Institute’s Cancer Systems Biology Consortium.

Proper citation: Harvard Medical School Center for Cancer Systems Pharmacology (RRID:SCR_022831) Copy   

•   Source: SciCrunch Registry

https://www.mitochondriasci.com/cancer.html

Creative Biogene provides comprehensive range of services and products to assist researchers in cancer related mitochondria studies. Offers tests and services with advantage of cell based and animal based models.

Proper citation: Creative Biogene Mitochondrial Gene Mutations (RRID:SCR_022082) 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