GO Tools: Search

AmiGO provides an interface to search and browse the ontology and annotation data provided by the GO consortium. Users can search for gene products and view the terms with which they are associated; alternatively, users can search or browse the ontology for GO terms of interest and see term details and gene product annotations. AmiGO also provides a BLAST search engine, which searches the sequences of genes and gene products that have been annotated to a GO term and submitted to the GO Consortium.

AmiGO accesses the GO mySQL database; more information is available from the GO database guide.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• slimmer-type tool
• term enrichment
• other analysis

Bioconductor provides tools for the analysis and comprehension of high-throughput (microarray, sequence, flow, etc.) genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. There are more than core and user-contributed 400 packages. Bioconductor packages the GO ontology into our semi-annual release, with software tools to: query; join with diverse additional gene, microarray, and sequence annotations; incorporate GO into annotation, differential expression, and gene set enrichment work flows; and visualize.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• software library
• statistical analysis
• term enrichment
• text mining
• other analysis
• Flexible integration of GO into statistical analysis and comprehension of high-throughput genetic data.

Gene Ontology For Functional Analysis (GOFFA) is a tool developed for ArrayTrack that takes a list of genes and identifies terms in Gene Ontology associated with those genes. GOFFA provides tools to view/access the following:
* GO term hierarchy
* Full listing of GO terms annotated with the genes associated with a given term
* Fisher's exact test p-value providing the probability of identifying that many genes for a given term by chance alone
* Relative enrichment factor (E-value) giving the enrichment of a GO term for genes in the submitted list relative to the frequency of genes assigned to that term from the full set of GOFFA annotated genes for a particular species

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• term enrichment
• text mining

Gene Ontology Normal Usage Tracking System (GONUTS) is a wiki-based system for using GO. GONUTS contains term pages where users can add or view notes elaborating on usage of GO terms. GONUTS also allows users to create and edit gene pages for any gene with a UniProt accession, and has tools to support annotation jamborees. GONUTS is the home of the CACAO (Community Assessment of Community Annotation with Ontologies) project to couple GO annotation to undergraduate education.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation editor

GeneTools is a collection of web-based tools that brings together information from a broad range of resources, and provides this in a manner particularly useful for genome-wide analyses. Today, the two main tools connected to this database are the NMC Annotation Database V2.0 and eGOn V2.0 (explore Gene Ontology).

The NMC Annotation Database V2.0 provides information from UniGene, EntrezGene, SwissProt and Gene Ontology (GO). Major features are:

• Single search/Batch search, extraction of data for single or batches of genes.
• Manage reporter lists: in folders and share selected lists with other users.
• Manual GO Annotation: add your own Gene Ontology (GO) annotations to genes of interest.
• Export: to Excel, text or XML format.

eGOn V2.0 facilitates interpretation of GO annotation. GO terms are retrieved in batch modus from EntrezGene and the GO database and displayed in the GO directed acyclic hierarchical graph (DAG). Essential features of eGOn V2.0 are:

• Visualization: gene annotations are visualized in the GO DAG or as a table view. The granularity of the GO DAG can be edited freely by the user.
• Filtering: GO annotations can be filtered on evidence codes.
• Include user defined GO annotations: previously added to the Annotation database.
• Statistical analysis: Several gene lists are analyzed simultaneously to compare the distribution of the annotated genes over the GO hierarchy.

Statistical tests are implemented to allow the user to compute GO annotation dissimilarity within or between gene lists.

• Connection to Annotation database: Links to Annotation database gene and protein information are offered directly from the GO DAG or in exported data.
• Export: GO DAG information, statistical results and gene and protein information can be exported in excel, text or XML format.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• statistical analysis
• term enrichment

GOanna is used to find annotations for proteins using a similarity search. The input can be a list of IDs or it can be a list of sequences in FASTA format. GOanna will retrieve the sequences if necessary and conduct the specified BLAST search against a user-specified database of GO annotated proteins. The resulting file contains GO annotations of the top BLAST hits. The sequence alignments are also provided so the user can use these to access the quality of the match.

• ontology or annotation search engine
• ontology or annotation editor

GORetriever is used to find all of the GO annotations corresponding to a list of user-supplied protein identifiers. GORetriever produces a list of proteins and their annotations and a separate list of entries with no GO annotation.

• ontology or annotation search engine

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.

• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• functional similarity
• semantic similarity
• other analysis
• comparative genomics analysis

With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization

OBO-Edit is an open source, platform-independent application 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.

OBO-Edit uses the OBO format flat file.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• ontology or annotation editor

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.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• other analysis
• compare commercially available microarrays based on GO

Many 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.

• 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 interest

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independently of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. We demonstrated the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer data sets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms (Draghici et.al, Genomics, 81(2), 2003). Other results obtained with Onto-Express can be found in Khatri et.al., Genomics. 79(2), 2002.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• statistical analysis
• term enrichment
• other analysis
• custom level of abstraction of the Gene Ontology

Onto-Express is a web-based tool in the Onto-Tools suite that performs automated function profiling for a list of differentially expressed genes. However, Onto-Express does not support functional profiling for the organisms that do not have annotations in public domain, or use of custom (i.e. user-defined) ontologies. This limitation is also true for most of the other existing tools for functional profiling (10), which means that researchers working with uncommon organisms and/or new annotations or ontologies may be forced to construct such profiles manually. Onto-Express To Go (OE2GO) is a new tool added to the Onto-Tools ensemble to address these issues. OE2GO is built on top of OE to leverage its existing functionality. In OE2GO, the users now have an option to use either the Onto-Tools database as a source of functional annotations or provide their own annotations in a separate file. Currently, OE2GO supports annotation file in the Gene Ontology format.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• statistical analysis
• term enrichment
• other analysis
• custom annotations, custom level of abstraction

Onto-Miner (OM) provide a single and convenient interface that allow the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages or 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.

• ontology or annotation search engine
• database or data warehouse
• other analysis
• scripted search of the Onto-Tools database for gene annotations

OntoVisT is a general purpose ontological visualization tool. Ontologies have emerged as a fast growing research topic in the area of semantic web during last decade. Currently there are 204 ontologies that are available through OBO Foundry and BioPortal. Several excellent tools for navigating the ontological structure are available, however most of them are dedicated to a specific annotation data or integrated with specific analysis applications, and do not offer flexibility in terms of general-purpose usage for ontology exploration.
We developed OntoVisT, a web based ontological visualization tool. This application is designed for interactive visualization of any ontological hierarchy for a specific node of interest, up to the chosen level of children and/or ancestor. It takes any ontology file in OBO format as input and generates output as DAG hierarchical graph for the chosen query. To enhance the navigation capabilities of complex networks, we have embedded several features such as search criteria, zoom in/out, center focus, nearest neighbor highlights and mouse hover events. The application has been tested on all 72 data sets available in OBO format through OBO foundry. The results for few of them can be accessed through OntoVisT-Gallery.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• in such a way that it contains both the property of DAG as well as placement of all child nodes below their parent nodes. The advantage of this representation is the flow of information is uni-directional, The tool is designed to improve the interpretability by modifying the structure in DAG hierarchical form, which reduces the effort to interpret the network.

PiNGO is 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.

• ontology or annotation search engine
• statistical analysis
• term enrichment
• functional similarity
• functional prediction

QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups. QuickGO offers a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• slimmer-type tool

RamiGO is a Bioconductor.org software package available for the statistical programming language R and provides an interface for sending requests to the AmiGO visualize web server, retrieving DAG GO trees, parsing GraphViz DOT format files, exporting GML files for Cytoscape and also for interactively displaying GO trees, received from AmiGO visualize, in Cytoscape without importing or exporting them.
RamiGO utilizes the visualization of GO trees from AmiGO and makes it available from R.

• ontology or annotation search engine
• ontology or annotation visualization
• other analysis

The Ontology Lookup Service (OLS) was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO) format.

• ontology or annotation browser
• ontology or annotation search engine