General concept

Current strain design algorithms are currently too costly to predict more than a few network modifications which would growth-couple the secretion of a product. This computation could be simplified using a local search gene deletion mutants with a desired phenotype can be iteratively improved through subsequent gene deletions, until a user defined number of alterations have been made. A heuristic approach is defined in which the user decides the k number of genetic manipulations and the number of M best solutions desired. Then MILP is use used to make at most k genetic changes and save the M best solutions. The M best solutions are used as new starting points for at most k changes. This is iterated until no more improved solutions are found. This method allows for faster computation of more complex gene modification sets, but may not find global optima.

Items to consider when implementing

Software packages with this method

Applications of interest

Description of study and link to study:

What was learned with this method:

Relevant references

Lun, et al.

Related methods

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