TR&D 2: MODELING MULTI-SCALE NETWORK ARCHITECTURE – PROJECT SUMMARY In this Technology Research and Development (TR&D) component, we advance methods to transition Network Biology from flat diagrams of nodes and edges towards multi-scale models of biological systems. Although current network models and layouts provide a useful summary of an interaction data set, these visualizations do not capture the exquisite multi-scale hierarchy of modular components and subcomponents that underlie many biological systems – from amino acids to proteins to protein complexes to biological processes to organelles, cells, and tissues. We recently demonstrated that detailed hierarchical information is embedded in, and systematically revealed by, biological network data. This discovery enabled us to reconstruct and extend the Gene Ontology hierarchy, yielding a GO based directly on molecular data (Data-Driven Ontologies) rather than literature. Here we seek to significantly increase the sensitivity and scalability of algorithms for detection of hierarchical network structure [Aim 1] and our ability to integrate many different lines of network evidence in building these hierarchies [Aim 2]. We also aim to broaden and generalize the concepts of hierarchical network analysis to study biological structure at the larger scales of cell populations and tissues [Aim 3]. Methods development is driven by an array of exciting Driving Biomedical Projects (DBPs) for which hierarchical modeling is a major need. These projects include large-scale mapping of human protein interactions with collaborators Krogan, Emili and Vidal (DBPs 1-3); genetic interaction mapping in yeast and human cell-cycle control pathways with Boone and Bienkowska (DBPs 4,11); regenerative medicine studies in multiple tissues (MedByDesign, DBP 6); and studies of cardiac tissue and its development (Chi, DBP 7). These efforts also invoke significant Technology Partnerships (TPs) with developers of biological ontologies and databases of gene function (Morris, Mungall, Mesirov, TPs 1-3) as well as experts in algorithms for network community detection (Fortunato, TP 4). Finally, underlying all of the above aims is the development of significant new software tools and services to enable a broad range of researchers to build, access and use biological systems hierarchies. Smart user interfaces (UIs) and services will be made available via a growing NRNB software ecosystem, including Cytoscape, NDEx, the Data-Driven Ontology Toolkit (DDOT), and the HiView Lens UI for hierarchy visualization and exploration.