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.