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http://www.arabidopsis.org/servlets/Search?type=keyword&action=new_search

TAIR Keyword Browser searches and browses for Gene Ontology, TAIR Anatomy, and TAIR Developmental stage terms, and allows you to view term details and relationships among terms. It includes links to genes, publications, microarray experiments and annotations associated with the term or any children terms. Platform: Online tool

Proper citation: TAIR Keyword Browser (RRID:SCR_005687) Copy   

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http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

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http://vortex.cs.wayne.edu/projects.htm#Onto-Miner

Onto-Miner (OM) provides a single and convenient interface that allows the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages of OM include the fact it allows queries with multiple genes and allows for scripting. This is unlike GenBank which uses a single gene navigation process. Scripted search of the Onto-Tools database for gene annotations. User account required. Platform: Online tool

Proper citation: Onto-Miner (RRID:SCR_005722) 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.pandora.cs.huji.ac.il/

With PANDORA, you can search for any non-uniform sets of proteins and detect subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA supports GO annotations as well as additional keywords (from UniProt Knowledgebase, InterPro, ENZYME, SCOP etc). It is also integrated into the ProtoNet system, thus allowing testing of thousands of automatically generated protein families. Note that PANDORA replaces the ProtoGO browser developed by the same group. Platform: Online tool

Proper citation: Pandora - Protein ANnotation Diagram ORiented Analysis (RRID:SCR_005686) Copy   

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http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

•   Source: SciCrunch Registry

https://syngoportal.org/

Evidence based, expert curated knowledge base for synapse. Universal reference for synapse research and online analysis platform for interpretation of omics data. Interactive knowledge base that accumulates available research about synapse biology using Gene Ontology annotations to novel ontology terms.

Proper citation: SynGO (RRID:SCR_017330) Copy   

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http://www.alliancegenome.org/

Organization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).

Proper citation: Alliance of Genome Resources (RRID:SCR_015850) Copy   

•   Source: SciCrunch Registry

http://tools.dice-database.org/GOnet/)

Web tool for interactive Gene Ontology analysis of any biological data sources resulting in gene or protein lists.

Proper citation: GOnet (RRID:SCR_018977) Copy   

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http://www.patika.org/

The human pathway database which contains different biological entities and reactions and software tools for analysis. PATIKA Database integrates data from several sources, including Entrez Gene, UniProt, PubChem, GO, IntAct, HPRD, and Reactome. Users can query and access this data using the PATIKAweb query interface. Users can also save their results in XML or export to common picture formats. The BioPAX and SBML exporters can be used as part of this Web service.

Proper citation: Pathway Analysis Tool for Integration and Knowledge Acquisition (RRID:SCR_002100) Copy   

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

The 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 compatible

Proper citation: Generic GO Term Mapper (RRID:SCR_005806) Copy   

•   Source: SciCrunch Registry

http://smd.stanford.edu/cgi-bin/source/sourceSearch

SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

•   Source: SciCrunch Registry

http://gdm.fmrp.usp.br/tools_bit.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. Gene Class Expression allows functional annotation of SAGE data using the Gene Ontology database. This tool performs searches in the GO database for each SAGE tag, making associations in the selected GO category for a level selected in the hierarchy. This system provides user-friendly data navigation and visualization for mapping SAGE data onto the gene ontology structure. This tool also provides graphical visualization of the percentage of SAGE tags in each GO category, along with confidence intervals and hypothesis testing. Platform: Online tool

Proper citation: Gene Class Expression (RRID:SCR_005679) Copy   

•   Source: SciCrunch Registry

http://vortex.cs.wayne.edu/projects.htm#Onto-Compare

Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Since focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the GO nomenclature. Compare commercially available microarrays based on GO. User account required. Platform: Online tool

Proper citation: Onto-Compare (RRID:SCR_005669) Copy   

•   Source: SciCrunch Registry

http://www.pathbase.net/

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   

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http://code.google.com/p/behavior-ontology

An ontology consisting of two main components, an ontology of behavioral processes and an ontology of behavioral phenotypes. The behavioral process branch of NBO contains a classification of behavior processes complementing and extending the GO process ontology. The behavior phenotype branch of NBO consists of a classification of both normal and abnormal behavioral characteristics of organisms. The prime application of NBO is to provide the vocabulary that is required to integrate behavior observations within and across species. It is currently being applied by several model organism communities as well as in the description of human behavior-related disease phenotypes. The main ontology is available in both the OBO Flatfile Format and the Web Ontology Language (OWL).

Proper citation: Neurobehavior Ontology (RRID:SCR_006201) Copy   

•   Source: SciCrunch Registry

http://owlapi.sourceforge.net/

The OWL API is a Java API and reference implementation for creating, manipulating and serializing OWL Ontologies. The latest version of the API is focused towards OWL 2. The OWLAPI underpins ontology browsing and editing tools and platforms such as SWOOP and Protege4. Note that this API, or any other OWL-based API, can be used without an integrated OWL parser if you download a pre-converted OWL file generated from OBO. See OBO Ontologies List for all OBO ontologies converted to OWL (we do not list the full complement of OWL-based APIs here, only those of direct relevance to GO). The OWL API includes the following components: * An API for OWL 2 and an efficient in-memory reference implementation * RDF/XML parser and writer * OWL/XML parser and writer * OWL Functional Syntax parser and writer * Turtle parser and writer * KRSS parser * OBO Flat file format parser * Reasoner interfaces for working with reasoners such as FaCT++, HermiT, Pellet and Racer Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWL API (RRID:SCR_005734) Copy   

•   Source: SciCrunch Registry

http://gsgator.ewha.ac.kr/

A web-based platform for functional interpretation of gene sets with features such as cross-species Gene Set Analysis (GSA), Flexible and Interactive GSA, simultaneous GSA for multiple gene set, and and a fully integrated network viewer for both visualizing GSA results and molecular networks.

Proper citation: gsGator (RRID:SCR_012035) Copy   

•   Source: SciCrunch Registry

http://www.cdtdb.brain.riken.jp/CDT/Top.jsp

Transcriptomic information (spatiotemporal gene expression profile data) on the postnatal cerebellar development of mice (C57B/6J & ICR). It is a tool for mining cerebellar genes and gene expression, and provides a portal to relevant bioinformatics links. The mouse cerebellar circuit develops through a series of cellular and morphological events, including neuronal proliferation and migration, axonogenesis, dendritogenesis, and synaptogenesis, all within three weeks after birth, and each event is controlled by a specific gene group whose expression profile must be encoded in the genome. To elucidate the genetic basis of cerebellar circuit development, CDT-DB analyzes spatiotemporal gene expression by using in situ hybridization (ISH) for cellular resolution and by using fluorescence differential display and microarrays (GeneChip) for developmental time series resolution. The CDT-DB not only provides a cross-search function for large amounts of experimental data (ISH brain images, GeneChip graph, RT-PCR gel images), but also includes a portal function by which all registered genes have been provided with hyperlinks to websites of many relevant bioinformatics regarding gene ontology, genome, proteins, pathways, cell functions, and publications. Thus, the CDT-DB is a useful tool for mining potentially important genes based on characteristic expression profiles in particular cell types or during a particular time window in developing mouse brains.

Proper citation: Cerebellar Development Transcriptome Database (RRID:SCR_013096) Copy   

•   Source: SciCrunch Registry