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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.
Database of histopathology photomicrographs and macroscopic images derived from mutant or genetically manipulated mice. The database currently holds more than 1000 images of lesions from mutant mice and their inbred backgrounds and further images are being added continuously. Images can be retrieved by searching for specific lesions or class of lesion, by genetic locus, or by a wide set of parameters shown on the Advanced Search Interface. Its two key aims are: * To provide a searchable database of histopathology images derived from experimental manipulation of the mouse genome or experiments conducted on genetically manipulated mice. * A reference / didactic resource covering all aspects of mouse pathology Lesions are described according to the Pathbase pathology ontology developed by the Pathbase European Consortium, and are available at the site or on the Gene Ontology Consortium site - OBO. As this is a community resource, they encourage everyone to upload their own images, contribute comments to images and send them their feedback. Please feel free to use any of the SOAP/WSDL web services. (under development)
Proper citation: Pathbase (RRID:SCR_006141) Copy
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
http://interactome.baderlab.org/
Project portal for the Human Reference Protein Interactome Project, which aims generate a first reference map of the human protein-protein interactome network by identifying binary protein-protein interactions (PPIs). It achieves this by systematically interrogating all pairwise combinations of predicted human protein-coding genes using proteome-scale technologies.
Proper citation: Human Reference Protein Interactome Project (RRID:SCR_015670) 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
https://software.broadinstitute.org/cancer/cga/polysolver
Software tool for HLA typing based on whole exome sequencing data and infers alleles for three major MHC class I genes. Enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using inferred alleles as reference.
Proper citation: Polysolver (RRID:SCR_022278) Copy
https://cytotrace.stanford.edu/
Software tool that predicts differentiation state of cells from single cell RNA sequencing data. Used for predicting differentiation states from scRNA-seq data.
Proper citation: CytoTRACE (RRID:SCR_022828) Copy
https://github.com/walaj/svaba
Software tool for detecting structural variants in sequencing data using genome wide local assembly. Genome wide detection of structural variants and indels by local assembly. Used for detecting SVs from short read sequencing data using genome wide local assembly with low memory and computing requirements.
Proper citation: SvABA (RRID:SCR_022998) Copy
Web application that helps design, evaluate and clone guide sequences for the CRISPR/Cas9 system. This sgRNA design tool assists with guide selection in a variety of genomes and pre-calculated results for all human coding exons as a UCSC Genome Browser track.
Proper citation: CRISPOR (RRID:SCR_015935) Copy
https://github.com/hetio/hetmatpy
Software Python package for matrix storage and operations on hetnets. Enables identifying relevant network connections between set of query nodes.
Proper citation: HetMatPy (RRID:SCR_023409) Copy
Web service to predict involvement of upstream cell signaling pathways, given signature of differentially expressed genes. Used to linking expression signatures to upstream cell signaling networks.
Proper citation: X2K Web (RRID:SCR_023624) Copy
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
Web platform for downstream analysis and visualization of proteomics data. Server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Primary input for server consists of set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values.
Proper citation: piNET (RRID:SCR_018693) Copy
Web service for querying or retrieving gene annotation data.
Proper citation: MyGene.info (RRID:SCR_018660) Copy
https://cistrome.shinyapps.io/timer/
Web server for comprehensive analysis of tumor infiltrating immune cells. Web tool for systematical analysis of immune infiltrates across diverse cancer types. Allows users to input function specific parameters, with resulting figures dynamically displayed to access tumor immunological, clinical, and genomic features.
Proper citation: TIMER (RRID:SCR_018737) Copy
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