We propose a framework to design metabolic pathways in which many objectives are optimized simultaneously. This allows to characterize the energy signature in models of algal and mitochondrial metabolism. The optimal design and assessment of the model is achieved through a multi-objective optimization technique driven by epsilon-dominance and identifiability analysis. A faster convergence process with robust candidate solutions is permitted by a relaxed Pareto dominance, regulating the granularity of the approximation of the Pareto front. Our framework is also suitable for black-box analysis, enabling to investigate and optimize any biological pathway modeled with ODEs, DAEs, FBA and GPR.
|Title of host publication||Proceedings of the 50th Annual Design Automation Conference, DAC 2013|
|Publication status||Published - 12 Jul 2013|
|Event||50th Annual Design Automation Conference - Austin, TX, United States|
Duration: 29 May 2013 → 7 Jun 2013
|Conference||50th Annual Design Automation Conference|
|Abbreviated title||DAC 2013|
|Period||29/05/13 → 7/06/13|