# National Resource for Network Biology (NRNB)

> **NIH NIH P41** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $1,202,095

## Abstract

OVERALL - PROJECT SUMMARY
The mission of the National Resource for Network Biology (NRNB) is to advance the science of biological
networks by creating leading-edge bioinformatic methods, software tools and infrastructure, and by engaging
the scientific community in a portfolio of collaboration and training opportunities. Much of biomedical research
is dependent on knowledge of biological networks of multiple types and scales, including molecular interactions
among genes, proteins, metabolites and drugs; cell communication systems; relationships among genotypes
and biological and clinical phenotypes; and patient and social networks. NRNB-supported platforms like
Cytoscape are among the most widely used software tools in biology, with tens of thousands of active users,
enabling researchers to apply network concepts and data to understand biological systems and how they are
reprogrammed in disease.
 NRNB’s three Technology Research and Development projects introduce innovative concepts with the
potential to transform network biology, transitioning it from a static to a dynamic science (TR&D 1); from flat
network diagrams to multi-scale hierarchies of biological structure and function (TR&D 2); and from descriptive
interaction maps to predictive and interpretable machine learning models (TR&D 3). In previous funding
periods our technology projects have produced novel and highly cited approaches, including network-based
biomarkers for stratification of disease, data-driven gene ontologies assembled completely from network data,
and deep learning models of cell structure and function built using biological networks as a scaffold.
 During the next period of support, we introduce dynamic regulatory networks formulated from single-cell
transcriptomics and advanced proteomics data (TR&D 1); substantially improved methodology for the study of
hierarchical structure and pleiotropy in biological networks (TR&D 2); and procedures for using networks to
seed machine learning models of drug response that are both mechanistically interpretable and transferable
across biomedical contexts (TR&D 3). These efforts are developed and applied in close collaboration with
outside investigators from 19 Driving Biomedical Projects who specialize in experimental generation of network
data, disease biology (cancer, neuropsychiatric disorders, diabetes), single-cell developmental biology, and
clinical trials. TR&Ds are also bolstered by 7 Technology Partnerships in which NRNB scientists coordinate
technology development with leading resource-development groups in gene function prediction, mathematics
and algorithm development, and biomedical databases. Beyond these driving collaborations, we continually
support a broader portfolio of transient (non-driving) research collaborations; organize and lead international
meetings including the popular Network Biology track of the Intelligent Systems for Molecular Biology
conference; and deliver a rich set of training opportunities and ...

## Key facts

- **NIH application ID:** 10401267
- **Project number:** 5P41GM103504-13
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Trey Ideker
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,202,095
- **Award type:** 5
- **Project period:** 2010-09-13 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10401267

## Citation

> US National Institutes of Health, RePORTER application 10401267, National Resource for Network Biology (NRNB) (5P41GM103504-13). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10401267. Licensed CC0.

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