Computer-aided techniques have been widely applied to analyse the biological circuits of microorganisms and facilitate rational modification of metabolic networks for strain design in order to maximise the production of desired biochemicals for metabolic engineering. Most existing computational methods for strain design formulate the network redesign as a bilevel optimisation problem. While such methods have shown great promise for strain design, this paper employs the idea of network interdiction to fulfil the task. Strain design as a Multiobjective Network Interdiction Problem (MO-NIP) is proposed for which two objectives are optimised (biomass and bioengineering product) simultaneously in addition to the minimisation of the costs of genetic perturbations (design costs). An initial approach to solve the MO-NIP consists on a Nondominated Sorting Genetic Algorithm (NSGA-II). The shown examples demonstrate the usefulness of the proposed formulation for the MO-NIP and the feasibility of the NSGA-II as a problem solver.
|Title of host publication
|Advances in Artificial Intelligence - 18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018, Proceedings
|Antonio Gonzalez, Alicia Troncoso, Francisco Herrera, Sergio Damas, Rosana Montes, Sergio Alonso, Oscar Cordon
|Number of pages
|Published - 2018
|18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018 - Granada, Spain
Duration: 23 Oct 2018 → 26 Oct 2018
|Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
|18th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2018
|23/10/18 → 26/10/18
Bibliographical noteFunding Information:
and TIN2017-86647-P from the Spanish Ministry of Economy and Competitiveness (including European Regional Development Funds). MT enjoys a Ph.D. research training staff grant associated with the project TIN2014-55024-P and co-funded by the European Social Fund.
SJ, MK, and NK acknowledge the EPSRC for funding project “Synthetic Portabolomics: Leading the way at the crossroads of the Digital and the Bio Economies (EP/N031962/1)”.
© Springer Nature Switzerland AG 2018.
- Metabolic networks
- Multiobjective bilevel optimisation
- Network interdiction
- Strain design