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Erschienen in:
2022 | OriginalPaper | Buchkapitel
MobsPy: A Meta-species Language for Chemical Reaction Networks
verfasst von : Fabricio Cravo, Matthias Függer, Thomas Nowak, Gayathri Prakash
Erschienen in: Computational Methods in Systems Biology
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Abstract
Chemical reaction networks are widely used to model biochemical systems. However, when the complexity of these systems increases, the chemical reaction networks are prone to errors in the initial modeling and subsequent updates of the model.
We present the Meta-species-oriented Biochemical Systems Language (MobsPy), a language designed to simplify the definition of chemical reaction networks in Python. MobsPy is built around the notion of meta-species, which are sets of species that can be multiplied to create higher-dimensional orthogonal characteristics spaces and inheritance of reactions. Reactions can modify these characteristics. For reactants, queries allow to select a subset from a meta-species and use them in a reaction. For products, queries specify the dimensions in which a modification occurs. We demonstrate the simplification capabilities of the MobsPy language at the hand of a running example and a circuit from literature. The MobsPy Python package includes functions to perform both deterministic and stochastic simulations, as well as easily configurable plotting. The MobsPy package is indexed in the Python Package Index and can thus be installed via
pip.