The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to each other. These term-term relationships encode how scientists conceive URLanization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternate natural way to group the functional terms which is different from the hierarchical structure established in the GO DAG. Instead of relying on an externally URLanization for biological functions, our method connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different biological experiments. Grouping terms by this alternate scheme  provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.
The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to each other. These term-term relationships encode how scientists conceive URLanization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternate natural way to group the functional terms which is different from the hierarchical structure established in the GO DAG. Instead of relying on an externally URLanization for biological functions, our method connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different experiments. We show that grouping terms by this alternate scheme is distinct from term relationships defined in the ontological structure and provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.
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biological experiments. Grouping
experiments. We show that grouping
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is distinct from term relationships defined in the ontological structure and