Finding New Order in Biological Functions from the Network Structure of Gene Annotations.
Finding New Order in Biological Functions from the Network Structure of Gene Annotations.
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DOI：
10.1371/journal.pcbi.1004565
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发表时间：
2015-11
影响因子：
4.3
通讯作者：
Girvan M
中科院分区：
文献类型：
--
作者：
Glass K;Girvan M
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 one another. These term-term relationships encode how scientists conceive the organization 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 alternative approach for grouping functional terms that captures intrinsic functional relationships that are not evident in the hierarchical structure established in the GO DAG. Instead of relying on an externally defined organization for biological functions, our approach connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different sources. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes. Investigating how a set of genes might collectively work together to perform various cellular processes has become a routine part of many biological analyses. In such analyses, genes of interest are compared to sets of genes annotated to various biological functions (or pathways) defined within carefully curated databases. One of the most comprehensive and widely used resources of this type is the Gene Ontology (GO) database. The Gene Ontology database is comprised of two important elements: (1) the ontology itself, which provides a controlled vocabulary of terms describing genetic function and also specifies how these functional terms are related to one another via a hierarchical structure; and (2) the set of annotations made using GO that connect individual genes to different functional terms. In our paper we investigate a method for organizing functional terms that results from connecting terms based on shared gene annotations. We find that this alternate classification has an organization that is highly distinct from the Gene Ontology hierarchy, challenging the way we think about the relationships between different biological functions. Finally, we show that these alternate collections of terms are highly associated with published cancer gene signatures, demonstrating that this alternative organization of biological functions can highlight important relationships between cellular processes and has the potential to lead to new insights and discoveries.
