# Control of biomolecular systems to guide cell phenotypes

> **NIH GM R35** · PENNSYLVANIA STATE UNIVERSITY, THE · 2026 · $400,969

## Abstract

Project Summary/Abstract
Phenotype control, an active area of research in network control, is applicable to interacting
biomolecular systems and can identify targeted interventions that lead to desired cell phenotypes.
Phenotype control distinguishes itself from classical control theory in that (i) its objectives are
related to dynamical attractors (e.g., stable states), and (ii) its interventions don’t need to be
continuously adjusted based on the state of the system. This type of control is well-suited for
guided cell differentiation, inducing cell fate changes, or inducing apoptosis of a target cell
population.
 This research program will further develop two phenotype control methods. Feedback
vertex set (FVS) control is based on the interaction network that underlies a biological system,
and stable motif (SM) control is based on a dynamic model of the system. The PI has participated
in the establishment of both of these methods, and has a track record of collaborative construction
of experimentally validated dynamic models of biological systems. This research program will
overcome the remaining challenge to the wide implementation of each phenotype control method.
The barrier to wide application of FVS control is that in many systems the characterization of the
target cell phenotype (e.g., the known state of a few biomarkers) is not sufficient to specify the
desired state of all FVS nodes. This barrier will be eliminated by identifying the most parsimonious
and sufficiently discerning characterization of each phenotype and extrapolating the existing
biological knowledge to achieve this characterization. The bottleneck to the wide application of
SM control is the long time needed for the development and verification of dynamic models.
Automating the key steps of model construction and refinement, building on the recently
developed BOOLean MOdel REfiner (boolmore) tool, will substantially decrease this time.
 The FVS and SM control methods will be implemented on n

## Key facts

- **NIH application ID:** 11259083
- **Project number:** 1R35GM161264-01
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** Reka Z Albert
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** GM
- **Fiscal year:** 2026
- **Award amount:** $400,969
- **Award type:** 1
- **Project period:** 2026-04-01T00:00:00 → 2031-01-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11259083

## Citation

> US National Institutes of Health, RePORTER application 11259083, Control of biomolecular systems to guide cell phenotypes (1R35GM161264-01). Retrieved via AI Analytics 2026-06-25 from https://api.ai-analytics.org/grant/nih/11259083. Licensed CC0.

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