Tech R and D_Theme3

University Of California, San Diego, La Jolla CA

Investigators

Linked publications & trials

Abstract

TRD 3: MULTI-SCALE NETWORKS ? PROJECT SUMMARY Although networks have been extremely useful for representing molecular interactions and mechanisms, network diagrams do not visually resemble the contents of cells. Rather, the cell involves a multi-scale hierarchy of components ? proteins are subunits of protein complexes which, in turn, are parts of pathways, biological processes, organelles, cells, tissues, and so on. In this Technology Research and Development Project (TRD), we will pursue methods that move Network Biology towards such hierarchical, multi-scale views of the structure and function of biological systems. Biological ontologies are one very successful framework for capturing hierarchical multi- scale organization, but they have so far been only indirectly connected to biological networks and other types of `omics data. Recently, we introduced methods for inferring the terms and term relations of a gene ontology directly from the hierarchical structure contained in molecular networks, and we prototyped a web resource to distribute network-based ontologies (NeXO, nexontology.org). This recent progress motivates and lays groundwork for our present focus on hierarchical multi-scale representations. Specific aims are to develop tools that: (1) Iteratively and flexibly incorporate new network experimental results into a `working' NeXO ontology, (2) Use a gene ontology structure, either inferred or literature curated, to guide an engine for generalized functional predictions, and (3) Explore multi-scale analysis above the cellular level, by bridging ligand-receptor networks to networks of cell- cell communication. These aims are stimulated by a range of Driving Biomedical Projects involving the Gene Ontology project, the Saccharomyces Genome Database, a Cancer Gene Ontology, and multi-scale analysis of viral-host, cell-cell communication and social networks. Ultimately, all research aims synergize to use network data to propel hierarchical models of biological structure and function.