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http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

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

OWLTools (aka OWL2LS - OWL2 Life Sciences) is a java API for accessing ontologies in either OBO or OWL. OWLTools provides a bio-ontologies friendly wrapper on top of the Manchester OWL API. It provides many features, including: * convenience methods for OBO-like properties such as synonyms, textual definitions, obsoletion, replaced_by * simple graph-like operations over ontologies * visualization using the QuickGO graphs libraries Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWLTools (RRID:SCR_005732) Copy   

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http://amigo.geneontology.org/

Web tool to search, sort, analyze, visualize and download data of interest. Along with providing details of the ontologies, gene products and annotations, features a BLAST search, Term Enrichment and GO Slimmer tools, the GO Online SQL Environment and a user help guide.Used at the Gene Ontology (GO) website to access the data provided by the GO Consortium. Developed and maintained by the GO Consortium.

Proper citation: AmiGO (RRID:SCR_002143) Copy   

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http://search.cpan.org/~cmungall/go-db-perl/

Software resource that extends the functionality of go-perl (on which it depends) with GO Database access functionality. go-db-perl comes bundled with various scripts and a shell command line interface that can be used as standalone tools. Installation is more involved than for go-perl; you will need a MySQL database plus the requisite DBI and DBD Perl modules. Full installation instructions are included in the download. go-db-perl is in use both to drive AmiGO and internally within Ensembl. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-db-perl (RRID:SCR_005721) Copy   

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http://search.cpan.org/~cmungall/go-perl/

go-perl is a set of Perl modules for parsing, manipulating and exporting ontologies and annotations. It includes parsers for the OBO and GO gene association file formats. It has a graph-based object model with methods for graph traversal. For more details, see the documentation included with the modules. go-perl comes bundled with XSL (Extensible Stylesheet Language) transforms (which can also be used independently of Perl, provided you have files in OBO-XML format), as well as scripts that can be used as standalone tools. Installation should be simple, provided you have some experience with Perl and CPAN; see the INSTALL file for details. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-perl (RRID:SCR_005730) Copy   

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http://oboedit.org/

OBO-Edit is an open source, platform-independent application written in Java for viewing and editing any OBO format ontologies. OBO-Edit is a graph-based tool; its emphasis on the overall graph structure of an ontology provides a friendly interface for biologists, and makes OBO-Edit excellent for the rapid generation of large ontologies focusing on relationships between relatively simple classes. The UI components are cleanly separated from the data model and data adapters, so these can be reused in other applications. The oboedit foward-chaining reasoner can also be used independently (for example, for traversing ontology graphs). OBO-Edit uses the OBO format flat file. See the GO wiki, http://wiki.geneontology.org/index.php/OBO-Edit:_Getting_the_Source_Code, for instructions on downloading the source code. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OBO-Edit (RRID:SCR_005668) Copy   

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http://gmod.org/wiki/Flash_GViewer

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

Proper citation: Flash Gviewer (RRID:SCR_012870) Copy   

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https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   

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http://bioconductor.org/packages/2.9/bioc/html/RamiGO.html

Software package with an R interface sending requests to AmiGO visualize, retrieving DAG GO trees, parsing GraphViz DOT format files and exporting GML files for Cytoscape. Also uses RCytoscape to interactively display AmiGO trees in Cytoscape.

Proper citation: RamiGO (RRID:SCR_006922) Copy   

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http://www.psb.ugent.be/esb/PiNGO/

A 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 compatible

Proper citation: PiNGO (RRID:SCR_000692) Copy   

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http://www.xspan.org/

COBrA is a Java-based ontology editor for bio-ontologies that distinguishes itself from other editors by supporting the linking of concepts between two ontologies, and providing sophisticated analysis and verification functions. In addition to the Gene Ontology and Open Biology Ontologies formats, COBrA can import and export ontologies in the Semantic Web formats RDF, RDFS and OWL. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: COBrA (RRID:SCR_005677) Copy   

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http://agbase.msstate.edu/cgi-bin/tools/goprofiler_select.pl

Service 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.

Proper citation: GOProfiler (RRID:SCR_005683) Copy   

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http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   

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http://www.blipkit.org/

Biomedical Logical Programming (Blip) is a research-oriented deductive database and prolog application library for handling biological and biomedical data. It includes packages for advanced querying of ontologies and annotations. Blip underpins the Obol tool. Here are some distinguishing characteristics of Blip * Lightweight. Bloat-free: Blip only has as many modules as it needs to do its job. * Fast. * Declarative. Say what you want to do, not how you want to do it * Blip can be Query-oriented: specify your data sources and ask your query * Blip can be Application-oriented: it is designed to be used as an application library used by other bioinformatics tools * Mature and fully functional ontology module for handling both OBO-style ontologies and OWL ontologies. * Modules for handling biological sequences and sequence features. (currently limited functionality, added as needed) * A systems biology module for querying pathway and interaction data. (currently limited functionality, added as needed) * Relational database integration. SQL can be viewed as a highly restricted dialect of Prolog. Although the SWI-Prolog in-memory database is fast and scalable, sometimes it is nice to be able to fetch data from an external database. Blip contains a generic SQL utility module and predicate mappings for the GO database, Ensembl and Chado * Integration with a variety of bioinformatics file formats. SWI-Prolog has a variety of fast libraries for dealing with XML, RDF and tabular data files. Blip provides bridges from bio file formats encoded using these syntaxes into its native models. For other syntaxes, Blip seamlessly integrates other packages such as BioPerl and go-perl. Although these dependencies require extra installation, there is no point reinventing the wheel * Rapid development of web applications. Blip extends SWI-Prolog''''s excellent http support with a simple and powerful logical-functional-programming style application server, serval. This has been used to prototype a fully-featured next-generation replacement for the GO project amigo browser. * Scalable. Blip is not intended to be a toy system on toy data (although it is happy to be used as a toy if you like!). It is intended to be used as an application component and a tool operating on real-world biological and biomedical data Blip is written in SWI-Prolog, a fast, robust and scalable implementation of ISO Prolog. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Blip: Biomedical Logic Programming (RRID:SCR_005733) Copy   

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http://www.ici.upmc.fr/cluego/

A Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ClueGO (RRID:SCR_005748) Copy   

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http://discover.nci.nih.gov/gominer/GoCommandWebInterface.jsp

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A 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.

Proper citation: High-Throughput GoMiner (RRID:SCR_000173) Copy   

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http://funsimmat.bioinf.mpi-inf.mpg.de

FunSimMat 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 tool

Proper citation: FunSimMat (RRID:SCR_002729) Copy   

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http://go.princeton.edu/cgi-bin/GOTermFinder

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy   

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http://apid.dep.usal.es

APID Interactomes (Agile Protein Interactomes DataServer) provides information on the protein interactomes of numerous organisms, based on the integration of known experimentally validated protein-protein physical interactions (PPIs). The interactome data includes a report on quality levels and coverage over the proteomes for each organism included. APID integrates PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. This collection references protein interactors, through a UniProt identifier.

Proper citation: Agile Protein Interactomes DataServer (RRID:SCR_008871) Copy   

•   Source: SciCrunch Registry

http://meme.nbcr.net/meme/cgi-bin/gomo.cgi

Gene Ontology for Motifs (GOMO) is an alignment- and threshold-free comparative genomics approach for assigning functional roles to DNA regulatory motifs from DNA sequence. The algorithm detects associations between a user-specified DNA regulatory motif (expressed as a position weight matrix; PWM) and Gene Ontology terms. The original method for predicting the roles of transcription factors (TFs starts with a PWM motif describing the DNA-binding affinity of the TF. GOMO uses the PWM to score the promoter region of each gene in the genome for its likelihood to be bound by the TF. The resulting ''''affinity'''' scores are then used to test each term in the Gene Ontology for association with high-scoring genes. The algorithm was subsequently extended to leverage conserved signals using multiple, related species in a comparative approach, which greatly improves the resulting annotations. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOMO - Gene Ontology for Motifs (RRID:SCR_008864) Copy   

•   Source: SciCrunch Registry