In this thesis, will be presented BioCAD, a novel computational tool able to design optimal and robust biological circuits. In BioCAD, the main idea is to use Pareto optimality and the Electronic Design Automation methods for Systems and Synthetic Biology.
However, BioCAD is a general purpose tool and can be seen as well as a black box able to receive in input a generic model and analyze its components and submodules, estimate its parameters, or optimize specific functions. BioCAD implements novel and state-of-the-art algorithms performing: (i) Optimization, by analyzing continuous, discrete or hybrid (continuous and discrete) variable spaces, for Single- and Multi-objective optimization problems and for local or global search; (ii) Sensitivity Analysis, for evaluating the importance of the parameters by ranking them according to their influence on the model; (iii) Robustness Analysis, for estimating the global and local fragility and robustness of optimal synthetic circuits; (iv) Identifiability Analysis, that finds functional relations among parameters, by analyzing the values of the decision variables after and before the optimization. Additionally, BioCAD implements the epsilon-dominance analysis, able to relax the Pareto condition and expand the solution space to neighborhood region of the Pareto surface. Optimization core contains novel tools for engineering enzymes, genes and fluxes in biological systems, while Sensitivity Analysis can reveal the main genes, enzymes, species or pathways.
BioCAD can be adopted and used with various modeling techniques: flux balance analysis with or without the gene protein reaction mappings, ordinary differential equations, differential algebraic equations and partial differential equations.
In this thesis will be reported several experiments applied on Synthetic Biology, such as the design of the novel 1,4-butanediol synthetic pathway
