Genetic Optimization Algorithm for Metabolic Engineering Revisited.

ABSTRACT: To date, several independent methods and algorithms exist for exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives, as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and the proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if th

SUBMITTER: Alter TB 

PROVIDER: S-EPMC6027426 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature