# TR&D 2 - Modeling Multi-Scale Network Architecture

> **NIH NIH P41** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $110,950

## Abstract

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.
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## Key facts

- **NIH application ID:** 9937489
- **Project number:** 2P41GM103504-11
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Trey Ideker
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $110,950
- **Award type:** 2
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9937489

## Citation

> US National Institutes of Health, RePORTER application 9937489, TR&D 2 - Modeling Multi-Scale Network Architecture (2P41GM103504-11). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9937489. Licensed CC0.

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