Issue 51, 2024

Mechanism-based and data-driven modeling in cell-free synthetic biology

Abstract

Cell-free systems have emerged as a versatile platform in synthetic biology, finding applications in various areas such as prototyping synthetic circuits, biosensor development, and biomanufacturing. To streamline the prototyping process, cell-free systems often incorporate a modeling step that predicts the outcomes of various experimental scenarios, providing a deeper insight into the underlying mechanisms and functions. There are two recognized approaches for modeling these systems: mechanism-based modeling, which models the underlying reaction mechanisms; and data-driven modeling, which makes predictions based on data without preconceived interactions between system components. In this highlight, we focus on the latest advancements in both modeling approaches for cell-free systems, exploring their potential for the design and optimization of synthetic genetic circuits.

Graphical abstract: Mechanism-based and data-driven modeling in cell-free synthetic biology

Article information

Article type
Highlight
Submitted
20 3 2024
Accepted
03 6 2024
First published
04 6 2024
This article is Open Access
Creative Commons BY license

Chem. Commun., 2024,60, 6466-6475

Mechanism-based and data-driven modeling in cell-free synthetic biology

A. Yurchenko, G. Özkul, N. A. W. van Riel, J. C. M. van Hest and T. F. A. de Greef, Chem. Commun., 2024, 60, 6466 DOI: 10.1039/D4CC01289E

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