Simulation and optimization of dynamic flux balance analysis models using an interior point method reformulation

Felipe Scott, Pamela Wilson, Raúl Conejeros, Vassilios S. Vassiliadis

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The proposed methodology utilizes transformation of the bounds of the embedded linear programming problem of flux balance analysis via a logarithmic barrier (interior point) approach. By exploiting the first-order optimality conditions of the interior-point problem, and with further transformations, the approach results in a system of implicit ordinary differential equations. Results from four case studies, show that the CPU and wall-times obtained using the proposed method are competitive with existing state-of-the art approaches for solving dFBA simulations, for problem sizes up to genome-scale. The differentiability of the proposed approach allows, using existing commercial packages, its application to the optimal control of dFBA problems at a genome-scale size, thus outperforming existing formulations as shown by two dynamic optimization case studies.
Original languageAmerican English
Pages (from-to)152-170
Number of pages19
JournalComputers and Chemical Engineering
Volume119
DOIs
StatePublished - 2 Nov 2018

Keywords

  • Dynamic flux balance analysis
  • Genome-scale metabolic network
  • Linear programming
  • Ordinary differential equations with embedded optimization

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