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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.
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
http://rnainformatics.org.cn/RiboToolkit/
Integrated web server developed for Ribo-seq data analysis. Platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution.Web based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs.
Proper citation: RiboToolkit (RRID:SCR_024406) Copy
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
https://seer.cancer.gov/lymphomarecode/lymphoma-2020.html
Website describing International Classification of Diseases codes that corresponds to lymphomas in the Surveillance, Epidemiology, and End Results (SEER) registry.
Proper citation: NCI Lymphoid Neoplasm Recode 2020 Revision Definition (RRID:SCR_024686) Copy
Software toolkit to run modern molecular simulations. It can be used either as a standalone application for running simulations, or as a library that enables accelerated calculations for molecular dynamics on high-performance computer architectures.
Proper citation: OpenMM (RRID:SCR_000436) Copy
Center for patient care, education and research on cancer. The institute focuses its research on prevention methods, early detection, treatment and finding cures.
Proper citation: Karmanos Cancer Institute (RRID:SCR_000508) Copy
http://discover.nci.nih.gov/gominer/
GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.
Proper citation: GoMiner (RRID:SCR_002360) Copy
Division of NCI that takes prospective cancer detection and treatment leads, facilitates their paths to clinical application, and expedites the initial and subsequent large-scale testing of new agents, biomarkers, imaging tests, and other therapeutic interventions (radiation, surgery, immunotherapy) in patients. DCTD, like all of NCI, supports many programs that could not be done without government funding - investigators supported by the division engage in scientifically sound, high-risk research that may yield great benefits for patients with cancer, but are too difficult or risky for industry or academia to pursue. This includes a particular emphasis on the development of distinct molecular signatures for cancer, refined molecular assays, and state-of-the-art imaging techniques that will guide oncologic therapy in the future. The division has eight major programs that work together to bring unique molecules, diagnostic tests, and therapeutic interventions from the laboratory bench to the patient bedside: * Cancer Diagnosis Program * Cancer Imaging Program * Cancer Therapy Evaluation Program * Developmental Therapeutics Program * Radiation Research Program * Translational Research Program * Biometrics Research Branch * Office of Cancer Complementary and Alternative Medicine
Proper citation: DCTD (RRID:SCR_004196) Copy
https://github.com/humanlongevity/HLA
Software tool for fast and accurate HLA typing from short read sequence data. Iteratively refines mapping results at amino acid level to achieve four digit typing accuracy for both class I and II HLA genes, taking only 3 min to process 30× whole genome BAM file on desktop computer.
Proper citation: xHLA (RRID:SCR_022277) Copy
https://github.com/RabadanLab/arcasHLA
Software tool for high resolution HLA typing from RNAseq. Fast and accurate in silico inference of HLA genotypes from RNA-seq.
Proper citation: arcasHLA (RRID:SCR_022286) Copy
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
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
THIS RESOURCE IS NO LONGER IN SERVICE. Doumented on September 23,2022. The National Cancer Institute initially established the Cooperative Prostate Cancer Tissue Resource (CPCTR) to provide prostate cancer tissue samples with clinical annotation to researchers. The Resource provides access to formalin-fixed, paraffin-embedded primary prostate cancer tissue with associated clinical and follow-up data for research studies, particularly studies focused on translating basic research findings into clinical application. Fresh-frozen tissue is also available with limited clinical follow up information since these are more recent cases. The Resource database contains pathologic and clinical information linked to a large collection of prostate tissue specimens that is available for research. Researchers can determine whether the Resource has the tissues and patient data they need for their individual research studies. Consultation and interpretive services: Assistance is available from trained CPCTR pathologists. The CPCTR can provide consultative assistance in staining interpretation, and scoring, on a collaborative basis. Fresh Frozen and Paraffin Tissue: The resource has over 7,000 annotated cases (including 7,635 specimens and 38,399 annotated blocks). Tissue Microarrays (TMA): The CPCTR has slides from prostate cancer TMAs with associated clinical data. The information provided for each case on the arrays (derived from radical prostatectomy specimens) includes: age at diagnosis, race, PSA at diagnosis, tumor size, TNM stage, Gleason score and grade, and vital status and other variables.
Proper citation: CPCTR: Cooperative Prostate Cancer Tissue Resource (RRID:SCR_000803) Copy
A biorepository for HIV-infected human biospecimens from a wide spectrum of HIV-related or associated diseases, including cancer, and from appropriate HIV-negative controls. The ACSR has formalin-fixed paraffin embedded biospecimens, fresh frozen biospecimens, malignant cell suspensions, fine needle aspirates, and cell lines from patients with HIV-related malignancies. It also contains serum, plasma, urine, bone marrow, cervical and anal specimens, saliva, semen, and multi-site autopsy speicmens from patients with HIV-related malignancies including those who have participated in clinical trials. The ACSR has an associated databank that contains prognostic, staging, outcome and treatment data on patients from whom tissues were obtained. The ACSR database contains more than 300,000 individual biospecimens with associated clinical information. Biospecimens are entered into the ACSR database by processing type, disease category, and number of cases defined by disease category.
Proper citation: AIDS and Cancer Specimen Resource (RRID:SCR_004216) Copy
http://www.bionet.umn.edu/tpf/home.html
Procure and distribute human tissue and other biological samples in support of basic, translational, and clinical cancer research at the University of Minnesota. The TPF is a centralized resource with standardized patient consent, sample collection, processing, storage, quality control, distribution, and electronic record maintenance. Since the 1996 inception of the TPF, over 61,000 tissue samples including well-preserved samples of malignant and benign tumors, organ-matched normal tissue, and other types of diseased tissues, have been collected from surgical specimens obtained at the University of Minnesota Medical Center-Fairview (UMMC-F) University Campus. Surgical pathologists are intellectually engaged in TPF functions, providing researchers with specimen-oriented medical consultation to facilitate research productivity. Prior to surgery, TPF personnel identify and consent patients for procurement of tissue, blood, urine, saliva, and ascites fluid. Within the integrated working environment of the surgical pathology laboratory, freshly obtained tissues not needed for diagnosis are selected and provided by pathologists to TPF personnel. Tissue samples are then assigned an independent code and processed. TPF staff can also work with researchers to individualize the procurement of tissues to fit specific research needs.
Proper citation: University of Minnesota Tissue Procurement Facility (RRID:SCR_004270) Copy
http://www.nsabp.pitt.edu/NSABP_Pathology.asp
The NSABP (National Surgical Adjuvant Breast and Bowel Project) Tissue Bank is the central repository of tissue samples (stained and unstained slides, tissue blocks, and frozen tissue specimens) collected from clinical trials conducted by the NSABP. The main scientific aim of the NSABP Division of Pathology is to develop clinical context-specific prognostic markers and predictive markers that predict response to or benefit from specific therapeutic modality. To achieve this aim, the laboratory collects the tumor and adjacent normal tissues from cancer patients enrolled into the NSABP trials through its membership institutions, and maintain these valuable materials with clinical follow-up information and distribute them to qualified approved investigators. Currently, specimens from more than 90,000 cases of breast and colon cancer are stored and maintained at the bank. Paraffin embedded tumor specimens are available from NSABP trials. We currently do not bank frozen tissues. All blocks are from patients enrolled in prospective NSABP treatment protocols and complete clinical follow up information as well as demographic information is available. Depending on the project, unstained tissue sections of 4-micrometer thickness, tissue microarrays, or stained slides are provided to the investigators in a blinded study format. Any investigators with novel projects that conform to the research goals of NSABP may apply for the tissue. Please refer to the NSABP Tissue Bank Policy to determine if your project conforms to these goals. Priority is given to NSABP membership institutions who regularly submit tissue blocks.
Proper citation: National Surgical Adjuvant Breast and Bowel Project Tissue Bank (RRID:SCR_004506) Copy
http://lussierlab.org/GO-Module/GOModule.cgi
GO-Module provides an interface to reduce the dimensionality of GO enrichment results and produce interpretable biomodules of significant GO terms organized by hierarchical knowledge that contain only true positive results. Users can download a text file of GO terms annotated with their significance and identified biomodules, a network visualization of resultant GO IDs or terms in PDF format, and view results in an online table. Platform: Online tool
Proper citation: GO-Module (RRID:SCR_005813) Copy
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
http://www.mc.vanderbilt.edu/root/vumc.php?site=chtn%20western%20division
The Cooperative Human Tissue Network- Western Division at Vanderbilt University Medical Center is one of six institutions throughout the country funded by the National Cancer Institutes to procure and distribute remnant human tissues to biomedical researchers throughout the United States and Canada. CHTN operates through a shared networking system which allows investigators greater access to available research specimens. CHTN offers a variety of preparation and preservation techniques to ensure investigators are receiving the quality specimens needed for research. Remnant tissues are obtained from surgical resections and autopsies and are procured to the specifications of the investigator.
Proper citation: Cooperative Human Tissue Network Western Division at Vanderbilt University Medical Center (RRID:SCR_006661) Copy
https://github.com/mikelove/tximport
Software R package for importing pseudoaligned reads into R for use with downstream differential expression analysis. Used for import and summarize transcript level estimates for transcript and gene level analysis.
Proper citation: tximport (RRID:SCR_016752) Copy
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