# Dynamics and evolution of synthetic and natural gene regulatory networks

> **NIH NIH R35** · STATE UNIVERSITY NEW YORK STONY BROOK · 2020 · $369,150

## Abstract

Project Summary: MIRA
Title: Dynamics and evolution of synthetic and natural gene regulatory networks
Tissues or microbial cell populations can consist of millions of cells, each of which contains billions of
molecules. Central among these molecules, DNA stores information in protein-coding genes, but also
in noncoding, gene-regulatory regions. Gene products binding to such regions form complex gene
regulatory networks that influence the behavior of individual cells and thereby cell populations.
Changes in DNA sequence can alter these networks, making cell populations better adapted in
various environments, contributing to genetic evolution. Yet, to learn how gene networks control cell
populations, we must understand how network dynamics and stochasticity affects cells and thereby
cell populations. Answering these questions should help us understand the behavior and evolution of
cell populations, which are the bases of cancer progression and microbial drug resistance.
To attack this problem, we have developed computational models of natural regulatory networks to
understand how they modulate nongenetic diversity in cell populations. We have also designed
synthetic gene networks to control the variability of protein expression in yeast and mammalian cells.
Now we plan to connect these research directions, using synthetic gene networks to generate specific
gene expression patterns in space and time that serve as signals for natural gene networks, studying
the subsequent effects on cell population behavior and evolution by computational modeling and
experimental evolution. Overall, these studies will shed light on how complex networks enable control
across scales of space and time in biology, from molecules to cells. Addressing these questions will
teach us how to control evolving cell populations, which is relevant for understanding, predicting and
possibly preventing cancer and microbial resistance.

## Key facts

- **NIH application ID:** 9897606
- **Project number:** 5R35GM122561-04
- **Recipient organization:** STATE UNIVERSITY NEW YORK STONY BROOK
- **Principal Investigator:** Gabor Balazsi
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $369,150
- **Award type:** 5
- **Project period:** 2017-04-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9897606

## Citation

> US National Institutes of Health, RePORTER application 9897606, Dynamics and evolution of synthetic and natural gene regulatory networks (5R35GM122561-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9897606. Licensed CC0.

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