Stochastic Differential Equations for Practical Simulation of Gene Circuits

Genetic circuit design is a well-studied problem in synthetic biology. Ever since the first genetic circuitsthe repressilator and the toggle switchwere designed and implemented, many advances have been made in this area of research. The current review systematically organizes a number of key works in this domain by employing the versatile framework of generalized morphological analysis. Literature in the area has been mapped on the basis of (a) the design methodologies used, ranging from bruteforce searches to control-theoretic approaches, (b) the modeling techniques employed, (c) various circuit functionalities implemented, (d) key design characteristics, and (e) the strategies used for the robust design of genetic circuits. We conclude our review with an outlook on multiple exciting areas for future research, based on the systematic assessment of key research gaps that have been readily unravelled by our analysis framework.

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Integrating mathematical modeling into synthetic biology education: a comprehensive approach through webinars and syllabus development

Boada,

Flores,

Vignoni

2024

Front. Educ.

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Mathematical modeling is a fundamental aspect of synthetic biology, enabling precise design and analysis of biological systems. To enhance students' understanding of this critical topic, we developed a series of webinars aimed at teaching mathematical modeling to iGEM teams. These webinars were initially created to maintain student engagement during a period of restricted lab access but quickly demonstrated their value as an effective educational tool. The success of these webinars highlighted the suitability of mathematical modeling as a topic well-suited to both onsite and online learning environments. Recognizing this, we expanded the content into a comprehensive syllabus for undergraduate courses in synthetic biology at the Universitat Politècnica de Valencia in Spain and Universidad de las Fuerzas Armadas—ESPE in Ecuador. The course now serves as a core component of synthetic biology education, offering students a robust framework for understanding and applying mathematical models. It includes a series of lectures, practical exercises, and case studies, all designed to deepen students' knowledge and skills in this essential area. To support educators and students, we have also developed a deck of slides and example scripts that provide practical examples and reinforce the concepts taught in the course. This manuscript presents the development, implementation, and impact of these educational initiatives, demonstrating how mathematical modeling can be effectively integrated into synthetic biology curricula to prepare students for real-world challenges in the field.

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Stochastic Differential Equations for Practical Simulation of Gene Circuits

Cited by 3 publications

References 36 publications

Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation

Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation

Designing Biological Circuits: From Principles to Applications

Integrating mathematical modeling into synthetic biology education: a comprehensive approach through webinars and syllabus development

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