Approximating an objective function with transcriptomic data

General concept

This approach modifies an objective function to fit new growth conditions in which the biomass composition changes. The original objective function is split into major metabolite components, and each component is sampled with MCMC to determine average reaction fluxes. In an iterative manner using linear regression, the components are removed or weighted and sampling was redone. This process is continued until sampling results fit the gene expression data.

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

Bordbar, et al.

Related methods

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