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

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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.

Original languageEnglish
Article number60
Pages (from-to)6466-6475
Number of pages10
JournalChemical Communications, ChemComm
Volume60
Issue number51
Early online date4 Jun 2024
DOIs
Publication statusPublished - 28 Jun 2024

Funding

FundersFunder number
European Commission
Engineering and Physical Sciences Research CouncilGA 101072980

    Keywords

    • Synthetic Biology/methods
    • Cell-Free System
    • Gene Regulatory Networks
    • Models, Biological

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