A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology

Modeling and simulating gene regulatory networks (GRNs) is crucial for understanding biological processes, predicting system behavior, interpreting experimental data and guiding the design of synthetic systems. In synthetic biology, GRNs are fundamental to enable the design and control of complex functions. However, GRN simulations can be time-consuming and often require specialized expertise. To address this challenge, we developed GRN_modeler - a user-friendly tool with a graphical user interface that enables users without programming experience to create phenomenological models, while also offering command-line support for advanced users. GRN_modeler supports the analysis of both dynamical behaviors and spatial pattern formation. We demonstrate its versatility through several examples in synthetic biology, including the design of novel oscillator families capable of robust oscillation with an even number of nodes, complementing the classical repressilator family, which requires odd-numbered nodes. Furthermore, we showcase how GRN_modeler allowed us to develop a light-detecting biosensor in Escherichia coli that tracks light intensity over several days and leaves a record in the form of ring patterns in bacterial colonies.

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Publication Details

Journal
Molecular Systems Biology
Published
2025-09-29
DOI
https://doi.org/10.1038/s44320-025-00148-8
Citations
3
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
2.42

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article

A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology

Erica Boni, Jung Hun Park, Yolanda Schaerli, Gábor Holló
3 citations
Molecular Systems Biology
Gene Regulatory Network Analysis
2.42
article

A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology

Erica Boni, Jung Hun Park, Yolanda Schaerli, Gábor Holló
article en
3 citations

Abstract

Modeling and simulating gene regulatory networks (GRNs) is crucial for understanding biological processes, predicting system behavior, interpreting experimental data and guiding the design of synthetic systems. In synthetic biology, GRNs are fundamental to enable the design and control of complex functions. However, GRN simulations can be time-consuming and often require specialized expertise. To address this challenge, we developed GRN_modeler - a user-friendly tool with a graphical user interface that enables users without programming experience to create phenomenological models, while also offering command-line support for advanced users. GRN_modeler supports the analysis of both dynamical behaviors and spatial pattern formation. We demonstrate its versatility through several examples in synthetic biology, including the design of novel oscillator families capable of robust oscillation with an even number of nodes, complementing the classical repressilator family, which requires odd-numbered nodes. Furthermore, we showcase how GRN_modeler allowed us to develop a light-detecting biosensor in Escherichia coli that tracks light intensity over several days and leaves a record in the form of ring patterns in bacterial colonies.

Molecular Systems BiologyVol. 21(11)
University of Lausanne (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Université de Lausanne
Openalex Percentile: Top 10%
Gene Regulatory Network Analysis
2.42
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