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http://www.rbta.es/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. Located in Spain, the Andalusian Regional Tumour Bank is a regional tumor bank. In the last decades cancer knowledge is growing exponentially due human genome knowledge and technological advantages. However, this disease is the biggest problem of health in Europe, with more than 2,5 million new cases per year. The diagnosis and treatment of cancer is now allowing to identify the characteristics that the disease has on each person. The next step is meant to be a great revolution in the treatment of cancer. This scientific development is dependent on the availability of human tumour samples preserved in demanding conditions. Current technology requires the availability of tissue morphological and molecular conditions similar to those that had the sample before being removed. Tumor banks are responsible for these new quality requirements to foster the development of research and health care of patients.

Proper citation: Andalusian Regional Tumour Bank (RRID:SCR_004885) Copy   

•   Source: SciCrunch Registry

https://htrn.osu.edu/Pages/Default.aspx

Collect, bank, and distribute human tissue and fluid specimens by uniting tissue-based research resources within the OSU Department of Pathology and promoting collaborative research within the OSU Medical Center and related national human research projects. The HTRN is comprised of the Pathology Core Facility (PCF), Tissue Archive Service (TAS), Tissue Procurement Service (TPS), AIDS and Cancer Specimen Resource (ACSR), the Cancer and Leukemia Group B Pathology Coordinating Office (CALGB - PCO), and an Adenoma Polyp Tissue Bank (APTB).

Proper citation: Human Tissue Resource Network (RRID:SCR_004785) Copy   

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http://www.bumc.bu.edu/busm-pathology/pathology-core-services/biospecimen-archive-research-core-barc/

Biospecimen repository of normal and diseased human material from a variety of tissues and conditions along with clinical annotation. Both frozen aliquots and paraffin embedded tissue are available. Biospecimens are available to qualified researchers with IRB approval. * Preliminary inquires please contact Cheryl Spencer at cheryl.spencer (at) bmc.org

Proper citation: Boston University Biospecimen Archive Research Core (RRID:SCR_005363) Copy   

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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://omniBiomarker.bme.gatech.edu

omniBiomarker is a web-application for analysis of high-throughput -omic data. Its primary function is to identify differentially expressed biomarkers that may be used for diagnostic or prognostic clinical prediction. Currently, omniBiomarker allows users to analyze their data with many different ranking methods simultaneously using a high-performance compute cluster. The next release of omniBiomarker will automatically select the most biologically relevant ranking method based on user input regarding prior knowledge. The omniBiomarker workflow * Data: Gene Expression * Algorithms: Knowledge-Driven Gene Ranking * Differentially expressed Genes * Clinical / Biological Validation * Knowledge: NCI Thesaurus of Cancer, Cancer Gene Index * back to Algorithms

Proper citation: omniBiomarker (RRID:SCR_005750) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29332&a=31537&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 4, 2014. Tissue Biobank collects samples from different types of cancers patients prospectively. Blood samples are being sent to KI Biobank for DNA extraction and storage. Number of sample donors: 611 (June 2010)

Proper citation: KI Biobank - Tissue Biobank (RRID:SCR_006043) 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   

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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://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

https://www.tissue-atlas.org/

Gathers together imaging and omic datasets into molecular maps of normal and diseased tissue from human and animal models, with emphasis on cancer. Used to access datasets, educational curriculum and talks, and recommended methods and software.

Proper citation: Harvard Tissue Atlas (RRID:SCR_022829) Copy   

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https://tabula-sapiens-portal.ds.czbiohub.org/

Single cell transcriptomic atlas of multiple organs from individual human donors. Multiple organ, single cell transcriptomic atlas of humans. Molecular reference atlas for cell types of human body. Provides molecular definition of these cell types and reveals many other aspects of human biology, including how same gene can be spliced differently in different cell types, how shared cell types in different tissues can have subtle differences in their identities, and how clones of immune system can be shared across tissues.

Proper citation: Tabula Sapiens (RRID:SCR_022314) Copy   

•   Source: SciCrunch Registry

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://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

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

https://github.com/wenmm/EssSubgraph/tree/main

A model algorithm that integrates omics data and network data to predict essential genes.

Proper citation: EssSubgraph (RRID:SCR_027354) 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