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Detalle de: Multi-objective mixed integer strategy for the optimisation of biological networks

Title Multi-objective mixed integer strategy for the optimisation of biological networks
Abstract

In this contribution, the authors consider multi-criteria optimisation problems arising from the field of systems biology when both continuous and integer decision variables are involved. Mathematically, they are formulated as mixed-integer non-linear programming problems. The authors present a novel solution strategy based on a global optimisation approach for dealing with this class of problems. Its usefulness and capabilities are illustrated with two metabolic engineering case studies. For these problems, the authors show how the set of optimal solutions (the so-called Pareto front) is successfully and efficiently obtained, providing further insight into the systems under consideration regarding their optimal manipulation.

Apa Reference Sendín, J. O. H., Exler, O., & Banga, J. R. (2010). Multi-objective mixed integer strategy for the optimisation of biological networks. IET Systems Biology, 4(3), 236–248. 10.1049/iet-syb.2009.0045
Doi 10.1049/iet-syb.2009.0045
Publication Date 13 May 2010
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Systems Biology, Network Biology
Research Groups Computational Biology Lab at MBG
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