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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.

(last updated: Aug 10, 2019)

Physical Resource or Software Tool Software

222 Results - per page

Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
FunSimMatResource, data analysis service, data access protocol, production service resource, analysis service resource, database, web service, service resource, software resource, data or information resourceFunSimMat is a comprehensive resource of semantic and functional similarity values. It allows ranking disease candidate proteins for OMIM diseases and searching for functional similarity values for proteins (extracted from UniProt), and protein families (Pfam, SMART). FunSimMat provides several different semantic and functional similarity measures for each protein pair using the Gene Ontology annotation from UniProtKB and the Gene Ontology Annotation project at EBI (GOA). There are several search options available: Disease candidate prioritization: * Rank candidate proteins using any OMIM disease entry * Compare a list of proteins to any OMIM disease entry * Compare all human proteins to any OMIM disease entry Functional similarity: * Compare one protein / protein family to a list of proteins / protein families * Compare a list of GO terms to a list of proteins / protein families Semantic similarity: * For a list of GO terms, FunSimMat performs an all-against-all comparison and displays the semantic similarity values. FunSimMat provides an XML-RPC interface for performing automatic queries and processing of the results as well as a RestLike Interface. Platform: Online toolfunctional similarity value, protein family, protein similarity, semantic similarity value, similarity value, functional similarity, disease gene candidate prioritization, disease, protein, protein family, disease candidate prioritization, semantic similarity, gene ontology, visualization, annotation, database or data warehouseSCR_002729(FunSimMat, RRID:SCR_002729)Max-Planck-Institute for Informatics; Saarbrucken; Germany European Union, German National Genome Research Network, Klinische Forschergrupperelated to: Gene Ontology, listed by: Gene Ontology ToolsReferences (2)Last checked upnif-0000-02860
GOProfilerResource, service resourceService that provides a summary of GO annotations available for each species. The user provides a taxon id and GOProfiler displays the number of GO associations and the number of annotated proteins for that species. The results are listed by evidence code and a separate list of unannotated proteins is also provided.ontology or annotation browser, annotation, protein, gene ontologySCR_005683(GOProfiler, RRID:SCR_005683)AgBase related to: Gene Ontology, listed by: Gene Ontology Tools, OMICtoolsPMID:16961921Last checked upnlx_149127, OMICS_02269
Generic GO Term MapperResource, data analysis service, data processing software, production service resource, analysis service resource, software application, service resource, software resourceThe Generic GO Term Mapper finds the GO terms shared among a list of genes from your organism of choice within a slim ontology, allowing them to be binned into broader categories. The user may optionally provide a custom gene association file or slim ontology, or a custom list of slim terms. The implementation of this Generic GO Term Mapper uses map2slim.pl script written by Chris Mungall at Berkeley Drosophila Genome Project, and some of the modules included in the GO-TermFinder distribution written by Gavin Sherlock and Shuai Weng at Stanford University, made publicly available through the GMOD project. GO Term Mapper serves a different function than the GO Term Finder. GO Term Mapper simply bins the submitted gene list to a static set of ancestor GO terms. In contrast, GO Term Finder finds the GO terms significantly enriched in a submitted list of genes. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatiblegene ontology, gene, gene association, slim ontology, slimmer-type tool, term enrichment, gene annotation, genomics, ontology, process, function, componentSCR_005806(Generic GO Term Mapper, RRID:SCR_005806)Princeton University; New Jersey; USA related to: Gene Ontology, Generic Model Organism Database Project, listed by: Gene Ontology ToolsLast checked upnlx_149294
MalaCardsResource, data or information resource, databaseAn integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. The database contains 17,705 diseases, consolidated from 28 sources.malady, annotation, gene, disease, cellular component, biological process, molecular function, expression profile, pathway, drug, compound, publication, phenotype, ortholog, gene ontologySCR_005817(MalaCards, RRID:SCR_005817)related to: Gene Ontology, Mouse Genome Informatics, DrugBank, KEGG, OMIM, PharmGKB, National Institute of Neurological Disorders and Stroke, Office of Rare Diseases Research, Bookshelf, MedlinePlus, Centers for Disease Control and PreventionLast checked upnlx_149314
CharProtDB: Characterized Protein DatabaseResource, data or information resource, databaseThe Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ??synonymous accessions??. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.protein, annotation, functional annotation, taxonomic classification, literature, gene ontology, evidence code, enzyme commission, transport classification, protein sequenceSCR_005872(CharProtDB: Characterized Protein Database, RRID:SCR_005872)J. Craig Venter Institute NHGRI, NIAIDrelated to: Gene OntologyPMID:22140108Last checked downnlx_149421
Tk-GOResource, software resourceTk-GO is a GUI wrapping the basic functions of the GO AppHandle library from BDGP. GO terms are presented in an explorer-like browser, and behavior can be configured by altering Perl scripts. All available documentation is included in the download. Tk-GO uses the GO database (connects directly to the BDGP database by default) but is user-configurable. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatiblebrowser, gene, ontology or annotation browserSCR_008855(Tk-GO, RRID:SCR_008855)Illumina related to: Gene Ontology, listed by: Gene Ontology ToolsLast checked upnlx_149133
MeGOResource, ontology, data or information resource, controlled vocabularyA Gene Ontology dedicated to the functions of mobile genetic elements. The terms defined are used to annotate phage and plasmid protein families in ACLAME. Note: The phage ontology PhiGO has now been incorporated in MeGO and can thus be accessed in MeGO version 1.0 and up.phage, plasmid, protein family, mobile genetic element, oboSCR_000110(MeGO, RRID:SCR_000110)A Classification of Mobile genetic Elements related to: OBO, AmiGO, Gene Ontology, listed by: BioPortalLast checked upnlx_156939
GenNavResource, analysis service resource, data analysis service, service resource, production service resourceGenNav searches GO terms and annotated gene products, and provides a graphical display of a term's position in the GO DAG. Platform: Online toolimage, gene, ontology or annotation browserSCR_000147(GenNav, RRID:SCR_000147)National Library of Medicine related to: Gene Ontology, listed by: Gene Ontology ToolsLast checked downnlx_149123
SynaptomeDBResource, data or information resource, databaseOntology-based knowledgebase for synaptic genes. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion / cytoskeletal proteins, scaffold proteins, transporters, and others. It integrates various and complex data sources for synaptic genes and proteins.gene, protein, pathway, synaptome, protein-protein interaction, synaptic gene, synapse, motif, presynaptic, postsynaptic, vesicleSCR_000157(SynaptomeDB, RRID:SCR_000157)Johns Hopkins University; Maryland; USA related to: Gene OntologyPMID:22285564Last checked downnlx_157656
High-Throughput GoMinerResource, data analysis service, production service resource, analysis service resource, web application, service resource, software resourceA web program that organizes lists of genes of interest (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology and automates the analysis of multiple microarrays then integrates the results across all of them in exportable output files and visualizations. High-Throughput GoMiner is an enhancement of GoMiner and is implemented with both a command line interface and a web interface. The program can also: efficiently perform automated batch processing of an arbitrary number of microarrays; produce a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories; integrate the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories; provide a fast form of false discovery rate multiple comparisons calculation; and provide annotations and visualizations for relating transcription factor binding sites to genes and GO categories.term enrichment, gene ontology, gene, microarray, common variable immune deficiency, high-throughput, visualization, databaseSCR_000173(High-Throughput GoMiner, RRID:SCR_000173)National Cancer Institute NCIrelated to: Gene Ontology, GoMiner, listed by: Gene Ontology ToolsPMID:15998470Last checked upnlx_149300
Onto-DesignResource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resourceMany Laboratories chose to design and print their own microarrays. At present, the choice of the genes to include on a certain microarray is a very laborious process requiring a high level of expertise. Onto-Design database is able to assist the designers of custom microarrays by providing the means to select genes based on their experiment. Design custom microarrays based on GO terms of interest. User account required. Platform: Online toolmicroarray, gene, biological process, molecular function, cellular component, data-mining, browser, visualization, analysis, design, search engine, ontology or annotation browser, ontology or annotation search engine, ontology or annotation visualization, database or data warehouse, other analysis, design custom microarrays based on go terms of interestSCR_000601(Onto-Design, RRID:SCR_000601)Wayne State University; Michigan; USA related to: Gene Ontology, listed by: Gene Ontology ToolsPMID:15215428Last checked downnlx_149109
OnEx - Ontology Evolution ExplorerResource, software resource, database, data or information resource, web applicationWeb-based application that integrates versions of 16 life science ontologies including the Gene Ontology, NCI Thesaurus and selected OBO ontologies with data leading back to 2002 in a common repository to explore ontology changes. It allows to study and apply the evolution of these integrated ontologies on three different levels. It provides global ontology evolution statistics and ontology-specific evolution trends for concepts and relationships and it allows the migration of annotations in case a new ontology version was releasedontology, gene, protein, function, process, component, ontology or annotation browser, evolution, trend, annotation, versionSCR_000602(OnEx - Ontology Evolution Explorer, RRID:SCR_000602)University of Leipzig; Saxony; Germany BMBF, DFGrelated to: Gene Ontology, NCI Thesaurus, OBO, listed by: OMICtools, Gene Ontology ToolsPMID:19678926Last checked upnlx_149129, OMICS_02273http://www.izbi.de/onex, http://aprilia.izbi.uni-leipzig.de:8080/onex/
AvadisResource, data analysis software, data processing software, software library, software application, data management software, data visualization software, software resource, software toolkit, commercial organizationAn integrated platform that provides analysis, management and visualization tools for next-generation sequencing data. It supports workflows for RNA-Seq, DNA-Seq, ChIP-Seq and small RNA-Seq experiments. Avadis has a built-in Gene Ontology browser to view ontology hierarchies. There are common ontology paths for multiple genes. Genes can be clustered based on ontology terms to identify functional signatures in gene expression clusters. AVADIS platform has a rich collection of data / text mining algorithms, data visualization libraries, workflow/application automation layers, and enterprise data organization functions. These functions are available as libraries that allow developers to rapidly build software prototypes, applications and off-the-shelf products. The collection of algorithms and visualizations in AVADIS grows as new applications using the platform are developed. Currently, the algorithms that AVADIS platform contains range from general purpose statistical mining and modelling algorithms, to text mining algorithms, to very application-specific algorithms for microarray / NGS data analysis, QSAR modelling and biological networks analysis. AVADIS has a collection of powerful mining algorithms like PCA, ANOVA, T-test, clustering, classification and regression methods. The range of visualizations includes most statistical and data modelling related graphing views, and very application-specific visualizations. Some of the statistical views include 2D/3D scatter plots, profile plots, heat maps, histograms and matrix plot; data modelling relevant views include dendrograms, cluster profiles, similarity images and SOM U-matrices. Application-specific views in AVADIS include pathway network views, genome browsers, chemical structure views and pipe-line views. Platform: Windows compatible, Mac OS X compatible, Linux compatible,gene expression, statistical analysis, gene ontology, ontology, gene, text mining, statistical mining, modelling, analysis, microarray, qsar modelling, biological network, pca, anova, t-test, clustering, classification, regression, data mining, visualization, rna-seq, dna-seq, chip-seq, alignment, next generation sequencing, small rna-seqSCR_000644(Avadis, RRID:SCR_000644)related to: Gene Ontology, listed by: Gene Ontology Tools, OMICtoolsLast checked upnlx_149208, nlx_149208, OMICS_01120http://www.strandls.com/Avadis
GONUTSResource, wiki, narrative resource, database, data or information resourceA wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase...ontology or annotation browser, ontology or annotation search engine, ontology or annotation editor, proteinSCR_000653(GONUTS, RRID:SCR_000653)EcoliHub NIGMSrelated to: Gene Ontology, listed by: Gene Ontology Tools, OMICtoolsPMID:22110029Last checked downnlx_30164, OMICS_02268
PiNGOResource, software resourceA Java-based tool to easily find unknown genes in a network that are significantly associated with user-defined target Gene Ontology (GO) categories. PiNGO is implemented as a plugin for Cytoscape, a popular open source software platform for visualizing and integrating molecular interaction networks. PiNGO predicts the categorization of a gene based on the annotations of its neighbors, using the enrichment statistics of its sister tool BiNGO. Networks can either be selected from the Cytoscape interface or uploaded from file. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatiblegene, annotation, network, candidate gene, biological network, ontology or annotation search engine, statistical analysis, term enrichment, functional similarity, functional prediction, search engine, windows, mac os x, linux, unixSCR_000692(PiNGO, RRID:SCR_000692)Ghent University; Ghent; Belgium related to: Gene Ontology, Cytoscape, listed by: Gene Ontology Tools, OMICtoolsPMID:21278188Last checked upnlx_149330, OMICS_02281
Automated Microarray PipelineResource, analysis service resource, data analysis service, service resource, production service resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented November 4, 2015. Web application based on the TM4 Microarray Software Suite to provide a means of normalization and analysis of microarray data. Users can upload data in the form of Affymetrix CEL files, and define an analysis pipeline by selecting several intuitive options. It performs data normalization (eg RMA), basic statistical analysis (eg t-test, ANOVA), and analysis of annotation using gene classification (eg Gene Ontology term assignment). The analysis are performed without user intervention and the results are presented in a web-based summary that allows data to be downloaded in a variety of formats compatible with further directed analysis.microarray, normalizationSCR_001219(Automated Microarray Pipeline, RRID:SCR_001219)TM4 NLMrelated to: Gene Ontology, listed by: OMICtoolsLast checked upOMICS_02125http://www.tm4.org/amp.html
categoryCompareResource, software resource, software application, data analysis software, data processing softwareA software package for meta-analysis of high-throughput experiments using feature annotations. It calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested).annotation, go, gene expression, multiple comparison, pathway, geneSCR_001223(categoryCompare, RRID:SCR_001223)Bioconductor related to: Gene Ontology, CRAN, uses: Cytoscape, listed by: OMICtoolsLast checked upOMICS_02122
globaltestResource, software resource, data processing software, data analysis software, sequence analysis software, software applicationA software package that tests groups of covariates (or features) for association with a response variable. The package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.differential expression, go, microarray, one channel, pathwaySCR_001256(globaltest, RRID:SCR_001256)Bioconductor related to: Gene Ontology, uses: KEGG, listed by: OMICtoolsLast checked upOMICS_02084
Semantic Measures LibraryResource, software resource, software toolkit, software libraryOpen source Java library dedicated to semantic measures computation and analysis. Tools based on the SML are also provided through the SML-Toolkit, a command line software giving access to some of the functionalities of the library. The SML and the toolkit can be used to compute semantic similarity and semantic relatedness between semantic elements (e.g. concepts, terms) or entities semantically characterized (e.g. entities defined in a semantic graph, documents annotated by concepts defined in an ontology).semantic measure, semantic similarity, semantic relatedness, functional similarity, gene ontology, annotation, parse, gene, disease ontology, mesh, rdf, owl, umls, snomed-ct, java, semantic, command lineSCR_001383(Semantic Measures Library, RRID:SCR_001383)Ecole des Mines d'Ales; Ales; France Ecole des Mines d'Ales; Ales; France, LGI2P Research Centerrelated to: Gene Ontology, listed by: FORCE11, Gene Ontology ToolsLast checked downnlx_152555
WegoLocResource, analysis service resource, data analysis service, service resource, production service resourceData analysis service that predicts protein subcellular localizations of animal, fungal, plant, and human proteins based on sequence similarity and gene ontology information.subcellular localization, proteinSCR_001402(WegoLoc, RRID:SCR_001402)related to: Gene Ontology, listed by: OMICtoolsLast checked upOMICS_01636
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