Conditional flux balance analysis toolbox for python
application to research metabolism in cyclic environments
Timothy Páez-Watson (TU Delft - Applied Sciences)
Ricardo Hernández Medina
Loek Vellekoop (Student TU Delft)
Mark C.M. van Loosdrecht (TU Delft - Applied Sciences)
S. Aljoscha Wahl (Friedrich-Alexander-Universität Erlangen-Nürnberg, TU Delft - Applied Sciences)
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Abstract
We present py_cFBA, a Python-based toolbox for conditional flux balance analysis (cFBA). Our toolbox allows for an easy implementation of cFBA models using a well-documented and modular approach and supports the generation of Systems Biology Markup Language models. The toolbox is designed to be user-friendly, versatile, and freely available to non-commercial users, serving as a valuable resource for researchers predicting metabolic behaviour with resource allocation in dynamic-cyclic environments.
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