Abstract
In this work, we calculate Elementary Flux Modes (EFMs) from metabolic networks using a trajectory-based metaheuristic, Variable Neighbourhood Search (VNS). This method is based on the local exploration around an incumbent solution and the subsequent visits to “neighbourhoods” (i.e., other areas of the search space) when the exploration is not successful on improving an objective function. This strategy ensures a suitable balance between exploration and exploitation, which is the key point in metaheuristic-based optimization. Making use of linear programming and the Simplex method, a VNS-based metaheuristic has been designed and implemented. This algorithm iteratively solves the linear programs resulting from the formulation of different hypotheses about the metabolic network. These solutions are, when feasible, EFMs. The application of the proposed method on a benchmark problem corroborates its efficacy.
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Acknowledgments
Author Jose A. Egea acknowledges the funding received from the Spanish Ministry of Economy and Competitiveness through the project “Multi-Scales” (DPI2011-28112-C04-04). This work was jointly supported by the Fundación Séneca (Agencia Regional de Ciencia y Tecnología, Región de Murcia) under grant 15290/PI/2010 and the Spanish MEC and European Commission FEDER under grant TIN2012-31345.
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Egea, J.A., García, J.M. (2016). Calculating Elementary Flux Modes with Variable Neighbourhood Search. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2016. Lecture Notes in Computer Science(), vol 9656. Springer, Cham. https://doi.org/10.1007/978-3-319-31744-1_27
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DOI: https://doi.org/10.1007/978-3-319-31744-1_27
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