Edit Paper: BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts

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Title*:	BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts
Authors*:	William Poole, Ayush Pandey, Andrey Shur, Zoltan Tuza, Richard M. Murray
Source*:	PLoS Computational Biology, 18(4), e1009987, 2022
Abstract*:	Biochemical interactions in systems and synthetic biology are often modeled with chemical reaction networks (CRNs). CRNs provide a principled modeling environment capable of expressing a huge range of biochemical processes. In this paper, we present a software toolbox, written in Python, that compiles high-level design specifications represented using a modular library of biochemical parts, mechanisms, and contexts to CRN implementations. This compilation process offers four advantages. First, the building of the actual CRN representation is automatic and outputs Systems Biology Markup Language (SBML) models compatible with numerous simulators. Second, a library of modular biochemical components allows for different architectures and implementations of biochemical circuits to be represented succinctly with design choices propagated throughout the underlying CRN automatically. This prevents the often occurring mismatch between high-level designs and model dynamics. Third, high-level design specification can be embedded into diverse biomolecular environments, such as cell-free extracts and in vivo milieus. Finally, our software toolbox has a parameter database, which allows users to rapidly prototype large models using very few parameters which can be customized later. By using BioCRNpyler, users ranging from expert modelers to novice script-writers can easily build, manage, and explore sophisticated biochemical models using diverse biochemical implementations, environments, and modeling assumptions.
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Edit Paper: BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts

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