Pareto epsilon-Dominance and Identifiable Solutions for BioCAD Modeling

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 optimizationtechniquedrivenbyepsilon-dominanceandidentifiability analysis. A faster convergence process with robust candidate solutions is permitted by a relaxed Pareto dominance, regulatingthegranularityoftheapproximationofthe 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. 1