Hybridization of Simulated Kalman Filter and Minimization of Metabolic Adjustment for Succinate and Lactate Production

Abstract

Metabolic engineering is a research discipline focused on constructing metabolic models and employing computational techniques in genetic modification to achieve enhanced production of specific phenotypes. The primary focus of this field is to maximize the production of the target metabolite using genetic engineering. Escherichia coli serves as a model organism in the production of succinate and lactate. In this research, in silico methods have been developed to be used to classify the knockout gene. The in silico method in this chapter is the hybrid of simulated Kalman filter (SKF) and the minimization of metabolic adjustment (MOMA). The hybrid method, SKFMOMA, will generate a list of gene knockouts, growth rates, and succinate and lactate production rates. The outcomes obtained from the hybrid method can be utilized in a practical wet laboratory experiment to enhance the production of succinate and lactate in E. coli.