The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. It is widely used by the biomedical research community for the analysis of -omics and related data. The GO knowledgebase includes experimental findings from almost 140,000 published papers, represented as over 600,000 experimentally-supported GO annotations. These annotations provide the core dataset for additional inference of over 6 million functional annotations for a diverse set of organisms spanning the tree of life. The GO knowledgebase has been expanded with new features and improvements, including developments that facilitate access to and application of the GO knowledgebase, and extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. The GO also includes software to edit and perform logical reasoning over the ontologies, web access to the ontology and annotations, and analytical tools that use the GO knowledgebase to support biomedical research. The GO ontology has been revised and expanded as biological knowledge accumulates. The ontology defines the universe of concepts relating to gene functions ('GO terms'), and how these functions are related to each other ('relations'). The GO ontology is constantly revised and expanded, with new terms and relations requested through online forms or GitHub trackers. Ontology updates are made collaboratively between the GOC ontology team and scientists who request the updates. The GO annotations consist of an association between a gene and a GO term, with supporting evidence in the form of a GO 'evidence code' and either a published reference or description of the methodology used to create the annotation. All GO annotations are ultimately supported by the scientific literature. The GO evidence codes describe the evidence and roughly reflect how far removed the annotated assertion is from direct experimental evidence. The GO has also been expanded with phylogenetically-inferred annotations, which are denoted by the IBA (Inferred from Biological Ancestry) evidence codes. These annotations are based on the relationships among genes inferred from evolutionary events. The GO has also been expanded with computationally-inferred annotations, which are denoted by the IEA (Electronic) evidence codes. The GO has also been expanded with gene-centric GO annotation sets, which use a single, standard identifier for each gene. The GO annotations are also available in a variety of formats, including a GAF file, which allows users to download large, highly customized sets of GO annotations. The GO has also been expanded with usability enhancements, including a new interactive ontology and annotation browser, and a new Matrix Tool that allows users to explore the overlaps between gene sets annotated to different GO classes. The GO has also been expanded with gene set enrichment analysis tools, which link directly to the interface at the PANTHER website. The GO has also been expanded with the ability to represent PubMed articles on the GO website, which allows users to access GO annotations while searching PubMed. The GO has also been expanded with the ability to represent biological models usingThe Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. It is widely used by the biomedical research community for the analysis of -omics and related data. The GO knowledgebase includes experimental findings from almost 140,000 published papers, represented as over 600,000 experimentally-supported GO annotations. These annotations provide the core dataset for additional inference of over 6 million functional annotations for a diverse set of organisms spanning the tree of life. The GO knowledgebase has been expanded with new features and improvements, including developments that facilitate access to and application of the GO knowledgebase, and extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. The GO also includes software to edit and perform logical reasoning over the ontologies, web access to the ontology and annotations, and analytical tools that use the GO knowledgebase to support biomedical research. The GO ontology has been revised and expanded as biological knowledge accumulates. The ontology defines the universe of concepts relating to gene functions ('GO terms'), and how these functions are related to each other ('relations'). The GO ontology is constantly revised and expanded, with new terms and relations requested through online forms or GitHub trackers. Ontology updates are made collaboratively between the GOC ontology team and scientists who request the updates. The GO annotations consist of an association between a gene and a GO term, with supporting evidence in the form of a GO 'evidence code' and either a published reference or description of the methodology used to create the annotation. All GO annotations are ultimately supported by the scientific literature. The GO evidence codes describe the evidence and roughly reflect how far removed the annotated assertion is from direct experimental evidence. The GO has also been expanded with phylogenetically-inferred annotations, which are denoted by the IBA (Inferred from Biological Ancestry) evidence codes. These annotations are based on the relationships among genes inferred from evolutionary events. The GO has also been expanded with computationally-inferred annotations, which are denoted by the IEA (Electronic) evidence codes. The GO has also been expanded with gene-centric GO annotation sets, which use a single, standard identifier for each gene. The GO annotations are also available in a variety of formats, including a GAF file, which allows users to download large, highly customized sets of GO annotations. The GO has also been expanded with usability enhancements, including a new interactive ontology and annotation browser, and a new Matrix Tool that allows users to explore the overlaps between gene sets annotated to different GO classes. The GO has also been expanded with gene set enrichment analysis tools, which link directly to the interface at the PANTHER website. The GO has also been expanded with the ability to represent PubMed articles on the GO website, which allows users to access GO annotations while searching PubMed. The GO has also been expanded with the ability to represent biological models using