Khanijou, J. K., Hee, Y. T., & Selvarajoo, K. (2023). Identifying Key In Silico Knockout for Enhancement of Limonene Yield Through Dynamic Metabolic Modelling. In Systems Biology (pp. 3–19). Springer US. https://doi.org/10.1007/978-1-0716-3577-3_1
Abstract:
Living cells display dynamic and complex behaviors. To understand their response and to infer novel insights not possible with traditional reductionist approaches, over the last few decades various computational modelling methodologies have been developed. In this chapter, we focus on modelling the dynamic metabolic response, using linear and non-linear ordinary differential equations, of an engineered Escherichia coli MG1655 strain with plasmid pJBEI-6409 that produces limonene. We show the systems biology steps involved from collecting time-series data of living cells, to dynamic model creation and fitting the model with experimental responses using COPASI software.
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Publisher Copyright
Funding Info:
This research / project is supported by the National Research Foundation, Singapore - Intra-create Thematic Grant “Cities” under the EcoCTs project.
Grant Reference no. : NRF2019-THE001-0007
Description:
This is a post-peer-review, pre-copyedit version of an article published in Methods in Molecular Biology. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-1-0716-3577-3_1