Ontology
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Gene Ontology
Gene Ontology (GO) database and informatics resource. The goal of the Gene Ontology Consortium is to produce a dynamic controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing.
GO PaD: the Gene Ontology Partition Database uses a new approach to gene enrichment analysis which maximises use of information, featuring ontology partitions with GO terms of similar specificity. GO PaD allows researchers can choose to analyze datasets at arbitrary levels of specificity. GO PaD features partition sets for functional analysis of genes from 11 commonly studied organisms (131,972 genes), and includes a tutorial. GO PaD addresses the use of Gene Ontology (GO) to infer function associated with sets of genes within large-scale automated genetic studies, which can sometimes incorrect conclusions miss discoveries.
Onto-Tools
Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Onto-Express is able to automatically translate lists of genes found to be differentially regulated in a given condition into functional profiles characterizing the impact of the condition studied upon various biological processes and pathways.Onto-Compare is a tool that allows efficient comparisons of any sets of commercial or custom arraysOnto-Design is a tool that allows the user to select genes that represent given functional categories. Onto-Translate allows the user to translate easily lists of accession numbers, UniGene clusters and Affymetrix probes into one another. All tools above are seamlessly integrated.
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OntoBlast
Derive potential functional annotations by ontology terms using sequence similarities. OntoBlast allows one to find information about potential functions of proteins by presenting a weighted list of ontology entries associated with similar sequences from completely sequenced genomes identified in a BLAST search. It combines, in a single analysis step, the search for sequence similarities in several species with the association of information stored in ontologies. From each identified ontology term a list of genes can be retrieved, which should share functional annotation.
ULMS
The Unified Medical Language System (UMLS): integrating biomedical terminology. The Unified Medical Language System is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP.
Genew
The Human Gene Nomenclature Database. Genew, the Human Gene Nomenclature Database is the only resource that provides data for all human genes that have approved symbols. It is managed by the HUGO Gene Nomenclature Committee (HGNC) as a confidential database, containing over 22 000 records, 75% of which are represented online by a publicly searchable text file. Since 2002, there have been significant improvements to the Genew search engine. Additionally we have increased our capacity to analyse confidential sequence data, which has enabled us to manage the large numbers of gene symbol requests that we receive from the chromosome sequencing consortia.
GO Annotation
The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology. The Gene Ontology Annotation (GOA) database aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60 000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort.
GoTree Machine Gene Ontology Tree Machine (GOTM or GoTree) - is a web-based platform for interpreting microarray data or other interesting gene sets using Gene Ontology hierarchies. GOTree Machine is a web-based platform for interpreting microarray data or other interesting gene sets using Gene Ontology hierarchies. GOTM currently works with human, mouse, rat and fly. Key features include (i) User friendly web-based interface (ii) Expandable tree for browsing the GO hierarchy, Fixed tree as HTML output for archive, Bar chart for publication (iii) Statistic analysis indicating GO terms with relatively enriched gene numbers and suggesting biological areas that warrant further study. Sub-tree and DAG visualizing enriched GO categories (iv) Retrieving subset of genes by GO term or keyword searching.
AmiGO Your friend in gene ontology. AmiGO is an HTML based application which allows the user to browse, query and visualize data from the Gene Ontology, or any ontology in OBO format. AmiGO can be accessed online at http://www.godatabase.org/cgi-bin/amigo/go.cgi. AmiGO is open source software and can be downloaded and installed as part of the go-dev cvs repository from the Gene Ontology sourceforge page.
GoStat Find statistically overrepresented GO terms within a group of genes. The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first.
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GoMiner GoMiner is a tool for biological interpretation of omic data – including data from gene expression microarrays. 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.
OBO Main Main.. Criteria.. Ontologies.. Browse.. Project.. CVS.. Subscribe.. Contact.. Open Biomedical Ontologies is an umbrella web address for well-structured controlled vocabularies for shared use across different biological and medical domains. ...
GO wiki
This wiki has been set up to provide unoffical documentation for users of the Gene Ontology Project.
