Using the hierarchy of biological ontologies to identify mechanisms in flat networks
- Citation data:
Biology & Philosophy, ISSN: 0169-3867, Vol: 32, Issue: 5, Page: 627-649
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- Arts and Humanities; Agricultural and Biological Sciences
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Systems biology has provided new resources for discovering and reasoning about mechanisms. In addition to generating databases of large bodies of data, systems biologists have introduced platforms such as Cytoscape to represent protein–protein interactions, gene interactions, and other data in networks. Networks are inherently flat structures. One can identify clusters of highly connected nodes, but network representations do not represent these clusters as at a higher level than their constituents. Mechanisms, however, are hierarchically organized: they can be decomposed into their parts and their activities can be decomposed into component operations. A potent bridge between flat networks and hierarchical mechanisms is provided by biological ontologies, both those curated by hand such as Gene Ontology (GO) and those extracted directly from databases such as Network Extracted Ontology (NeXO). I examine several examples in which by applying ontologies to networks, systems biologists generate new hypotheses about mechanisms and characterize these novel strategies for developing mechanistic explanations.