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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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http://clinicalinformatics.stanford.edu/services/biobank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 7th, 2023. An online, searchable record of biospecimen attributes and storage location for the following three biobanks at Stanford: * The Bone Marrow Transplant (BMT) program * The Hematology biospecimen bank is a research sample repository focusing on blood, plasma and bone marrow, primarily from leukemia patients. * Cancer Center Pathology Core: The Stanford Comprehensive Cancer Center Tissue Bank stores research samples of both solid tumor and blood from cancer patients, with an emphasis on prostate. As of November 2009, the system contains data on 50,000 biospecimens stored in multiple banks at Stanford. An anonymous Biospecimen Locator allows Stanford researchers to search the STRIDE Virtual Biospecimen Bank for suitable samples without having to know, or expose, any protected patient-specific information. Having determined that suitable specimens exist in one of the constituent biospecimens banks, the researcher can generate a Web-based request form to obtain additional information from the appropriate bank operator(s). Access to specimens is restricted to Stanford Faculty and Staff or affiliates., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: STRIDE Virtual Biospecimen Bank (RRID:SCR_008667) Copy   


https://portal.gdc.cancer.gov/

A unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.

Proper citation: Genomic Data Commons Data Portal (GDC Data Portal) (RRID:SCR_014514) Copy   


http://www.fccc.edu/prevention/studies/biosample/about.html

Fox Chase has developed a facility dedicated to the collection and distribution of human subject biosamples and supporting personal and family cancer history data. In response to announcement (CA-00-025; P30 CA06927S2), the Fox Chase Cancer Center''s Biosample Repository (BR) and Tumor Bank Facility (TBF) is making blood specimens (i.e., whole blood, plasma, platelet-rich plasma, platelet homogenates, red blood cells, leukocytes, lymphoblastoid cell lines, and DNA isolated from leukocytes) and tumor tissues (i.e., multi-tissue microarrays and tumor DNAs) collected by our facilities available for research. Request for blood and tissue will be reviewed by a panel of scientists and ranked. Priority will be given to those investigators with current NIGH/NCI funding, but will be made available as recommended by the internal and external advisory committees. * Blood Inventory: Plasma, Serum, Whole Blood, Lymphocytes, DNA * Tissue Inventory: Tumor and Normal Adjacent Tissue, Fresh-Frozen, Formalin-Fixed Paraffin-Embedded Tissue, OCT Embedded Tissue, Ethanol-fixed Tissue

Proper citation: Fox Chase Biosample Repository Core Facility (RRID:SCR_004746) Copy   


http://www.bccrc.ca/dept/ttr

A provincial biobank resource to support translational cancer research at the BC Cancer Agency, across Canada and internationally. This biobank collects biospecimens (tissues and blood), and clinical information and processes these to create anonymous cases that can be studied by cancer researchers to understand how cancer develops, how it grows, how it spreads, and how it responds to treatment. These tissues and data are obtained from patients who undergo surgery to treat a tumor and who have generously provided their consent for the TTR to collect tissues that are unused after diagnosis has been completed. The TTR is a provincial program that currently comprises a core biobank at the Vancouver Island Center, Victoria, that offers participation in the program to patients in Victoria and Nanaimo. The TTR works with other banks and expert translational research groups in BC, to create expanded capacity for collection and opportunities for research access to tissue resources. The TTR operates under the management and oversight of the director, a scientific advisory board, and the UBC BCCA Research Ethics Board. The TTR operates within organizational policies and a commitment to protection of donor privacy that is embodied in all standard operating procedures and aspects of the repository. The TTR is also a founding member and contributor to the development of provincial (BC BioLibrary) and national (CTRNet) initiatives to promote biobanking.

Proper citation: British Columbia Tumour Tissue Repository (RRID:SCR_004597) Copy   


  • RRID:SCR_018273

    This resource has 100+ mentions.

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   


  • RRID:SCR_019127

    This resource has 1+ mentions.

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   


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   


  • RRID:SCR_021722

    This resource has 500+ mentions.

https://dcc.icgc.org/

Portal provides tools for visualizing, querying, and downloading cancer data, which is released on quarterly schedule.

Proper citation: ICGC Data Portal (RRID:SCR_021722) Copy   


  • RRID:SCR_006053

    This resource has 10+ mentions.

https://array.nci.nih.gov/caarray/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on Sep 18, 2018. Open-source, web and programmatically accessible microarray data management system. caArray guides the annotation and exchange of array data using a federated model of local installations whose results are shareable across the cancer Biomedical Informatics Grid (caBIG). caArray furthers translational cancer research through acquisition, dissemination and aggregation of semantically interoperable array data to support subsequent analysis by tools and services on and off the Grid. As array technology advances and matures, caArray will extend its logical library of assay management.

Proper citation: caArray (RRID:SCR_006053) Copy   


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   


  • RRID:SCR_012815

    This resource has 1000+ mentions.

http://www.ukbiobank.ac.uk/

Biobank provides data collected at Assessment Center and via online questionnaires on participants aged 40-69 years recruited throughout United Kingdom and provides summary information to improve prevention, diagnosis and treatment of serious and life threatening illnesses.

Proper citation: UK Biobank (RRID:SCR_012815) Copy   


  • RRID:SCR_013275

    This resource has 10+ mentions.

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   


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   


http://www.cancerimagingarchive.net/

Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.

Proper citation: Cancer Imaging Archive (TCIA) (RRID:SCR_008927) Copy   


http://www.ncibi.org/

The Center develops conceptual models, computational infrastructure, an integrated knowledge repository, and query and analysis tools that enable scientists to effectively access and integrate the wealth of biological data. The National Center for Integrative Biomedical Informatics (NCIBI) was founded in October 2005 and is one of seven National Centers for Biomedical Computing (NCBC) in the NIH Roadmap. NCIBI is based at the University of Michigan as a part of the Center for Computational Medicine and Biology (CCMB). NCIBI is composed of biomedical researchers, computational biologists, computer scientists, developers and human-computer interaction specialists organized into seven major core functions. They work in interdisciplinary teams to collectively develop tools that are not only computationally powerful but also biologically relevant and meaningful. The four initial Driving Biological Projects (prostate cancer progression, Type 1 and type 2 diabetes and bipolar disorder) provide the nucleation point from which tool development is informed, launched, and tested. In addition to testing tools for function, a separate team is dedicated to testing usability and user interaction that is a unique feature of this Center. Once tools are developed and validated the goal of the Center is to share and disseminate data and software throughout the research community both internally and externally. This is achieved through various mechanisms such as training videos, tutorials, and demonstrations and presentations at national and international scientific conferences. NCIBI is supported by NIH Grant # U54-DA021519.

Proper citation: National Center for Integrative Biomedical Informatics (RRID:SCR_001538) Copy   


  • RRID:SCR_023931

    This resource has 1+ mentions.

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   


  • RRID:SCR_006307

    This resource has 1000+ mentions.

https://www.synapse.org/

A cloud-based collaborative platform which co-locates data, code, and computing resources for analyzing genome-scale data and seamlessly integrates these services allowing scientists to share and analyze data together. Synapse consists of a web portal integrated with the R/Bioconductor statistical package and will be integrated with additional tools. The web portal is organized around the concept of a Project which is an environment where you can interact, share data, and analysis methods with a specific group of users or broadly across open collaborations. Projects provide an organizational structure to interact with data, code and analyses, and to track data provenance. A project can be created by anyone with a Synapse account and can be shared among all Synapse users or restricted to a specific team. Public data projects include the Synapse Commons Repository (SCR) (syn150935) and the metaGenomics project (syn275039). The SCR provides access to raw data and phenotypic information for publicly available genomic data sets, such as GEO and TCGA. The metaGenomics project provides standardized preprocessed data and precomputed analysis of the public SCR data.

Proper citation: Synapse (RRID:SCR_006307) Copy   


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   


  • RRID:SCR_002657

    This resource has 100+ mentions.

https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   


  • RRID:SCR_006454

    This resource has 10+ mentions.

http://lincs.hms.harvard.edu/db/

Database that contains all publicly available HMS LINCS datasets and information for each dataset about experimental reagents and experimental and data analysis protocols. Experimental reagents include small molecule perturbagens, cells, antibodies, and proteins.

Proper citation: HMS LINCS Database (RRID:SCR_006454) Copy   



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