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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   

•   Source: SciCrunch Registry

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   

•   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

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://www.cpctr.net/

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   

•   Source: SciCrunch Registry

http://pluto3.nci.nih.gov/tissue/default.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Specimen Resource Locator is a database to help researchers locate human specimens (tissue, serum, DNA/RNA, other specimens) for cancer research. It includes tissue banks and tissue procurement systems with access to normal, benign, precancerous and cancerous human tissue from a variety of organs. Researchers specify the types of specimens, number of cases, preservation methods and associated data they require. The Locator will then search the database and return a list of tissue resources most likely to meet their requirements. When no match is obtained, the researcher is referred to the NCI Tissue Expediter (tissexp@mail.nih.gov). The Tissue expediter is a scientist who can help researchers identify appropriate resources and/or appropriate collaborators.

Proper citation: NCI Specimen Resource Locator (RRID:SCR_004754) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://worfdb.dfci.harvard.edu/

Database that integrates and disseminates the data from the cloning of complete set of predicted protein-encoding ORFs of Caenorhabditis elegans. It also allows the community to search for availability and quality of cloned ORFs. So far, ORF sequence tags (OSTs) obtained for all individual clones have allowed exon structure corrections for ORFs originally predicted by the C. elegans sequencing consortium. The database contains this OST information along with data pertinent to the cloning process.

Proper citation: WorfDB (RRID:SCR_006028) 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://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://www.pathology.med.ohio-state.edu/HTRN/apc/default.asp

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The Adenoma Polyp Tissue Bank (APTB) receives whole blood from patients enrolled in the Prevention of Sporadic Colorectal Adenomas with Celecoxib clinical trial. We have reached our accrual on blood submissions, so we will no longer be receiving blood specimens The objectives of this trial are as follows: A. To determine the efficacy and safety of celecoxib versus placebo in preventing the occurrence of newly detected colorectal adenomas in subjects at increased risk for colorectal carcinoma. In addition to incidence, other established risk factors will be evaluated for their association with occurrence of new colorectal adenomas, including cancer family history and adenoma size, histopathologic grade, multiplicity and location. Primary assessment of treatment efficacy will be the reduction in the number of subjects with adenomas at colonoscopy after Year 1 and Year 3 of study drug use. Secondary assessments of treatment efficacy will be 1) the number of adenomas 2) the histopathologic grade of adenomas and 3) the size of adenomas, also measured after one year and three years of study drug use. These factors will be incorporated into a risk model for predicting adenoma occurrence and response to celecoxib. B. To determine the efficacy of celecoxib versus placebo in modulating one or more of a panel of biomarkers for colorectal cancer at the cellular and molecular level sampled in a subset of subjects at selective sites at baseline and after Year 1 and Year 3 of study drug use. These biomarkers will include measurements of aberrant crypt foci (ACF), proliferation (index and crypt distribution), apoptosis (index and crypt distribution), COX expression and activity. If modulation of one or more mucosal biomarkers occur, we will explore whether it correlates with the development of incident colorectal neoplasia (adenomas/carcinomas), thereby attempting to validate the surrogacy of that biomarker. C. To develop a specimen bank. Serum and white blood cells are isolated from whole blood and adenoma tissue blocks and slides are banked. Banked specimens will become available for use in correlative science studies at a later point. This project began in 1999 and will be extended through 2006. The lead principal investigator is Monica M. Bertagnolli, MD, Brigham and Women''s Hospital, Boston, MA, and the APTB Director is Scott Jewell, Ph.D., Department of Pathology, The Ohio State University. The APTB is supported by the NIH, NCI Division of Cancer Prevention, in connection with the Strang Cancer Prevention Center, Cornell University, New York., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Adenoma Polyp Tissue Bank (RRID:SCR_005366) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/annotare/

A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.

Proper citation: Annotare (RRID:SCR_000319) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/nondetects.html

Software R package to model and impute non-detects in results of qPCR experiments.Used to directly model non-detects as missing data.

Proper citation: nondetects (RRID:SCR_001702) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/exonarray/cgi-bin/plot_selector.pl

Transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes. Provides improved cell-type-specific markers for better understanding of neural development, function, and disease.

Proper citation: Exon Array Browser (RRID:SCR_008712) Copy   

•   Source: SciCrunch Registry

http://www.rhesusbase.org/drugDisc/CAM.jsp

OKCAM (Ontology-based Knowledgebase for Cell Adhesion Molecules) is an online resource for human genes known or predicted to be related to the processes of cell adhesion. These genes include members of the cadherin, immunoglobulin/FibronectinIII (IgFn), integrin, neurexin, neuroligin, and catenin families. Totally 496 human CAM genes were compiled and annotated. We have mapped these genes onto a novel cell adhesion molecule ontology (CAMO) that provides a hierarchical description of cell adhesion molecules and their functions. It is intended to provide a means to facilitate better and better understanding of the global and specific properties of CAMs through their genomic features, regulatory modes, expression patterns and disease associations become clearer. You may browse by CAM ontology, Chromosomes and Full Gene list.

Proper citation: OKCAM: Ontology-based Knowledgebase for Cell Adhesion Molecules (RRID:SCR_010696) 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://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://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://www.gem-beta.org/Public/Home.aspx

Database that contains behavioral and social science measures organized by theoretical constructs. GEM is designed to enable researchers to use common measures with the goal of exchanging harmonized data.

Proper citation: Grid-Enabled Measures Database (RRID:SCR_016043) Copy   

•   Source: SciCrunch Registry