Conference Paper

# Multi-Objective Optimization of Biological Networks for Prediction of Intracellular Fluxes.

DOI: 10.1007/978-3-540-85861-4_24 In proceeding of: 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics, IWPACBB 2008, Salamanca, Spain, 22th-24th October 2008

Source: DBLP

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**ABSTRACT:**Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different "environments" (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks.PLoS ONE 01/2012; 7(7):e41122. · 3.73 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**Constructing biological circuits in a bottom-up modular fashion using design methodologies similar to those used in electronics has gained tremendous attention in the past decade. The end goal, however, is engineering biological systems and not only individual components in the context of pursuing applications useful in improving human health or enhancing the environment. This article reviews the basics of biological system design rooted in Metabolic Engineering and Systems Biology and outlines current system-level modeling, analysis, optimization, and synthesis with emphasis on some current bottlenecks in establishing more rigorous design tools and methodologies for engineering biological systems.01/2012; -
##### Article: Robust Design of Microbial Strains.

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**ABSTRACT:**MOTIVATION: Metabolic engineering algorithms provide means to optimise a biological process leading to the improvement of a biotechnological interesting molecule. Therefore, it is important to understand how to act in a metabolic pathway in order to have the best results in terms of productions. In this work, we present a computational framework that searches for optimal and robust microbial strains that are able to produce target molecules. Our framework performs three tasks: it evaluates the parameter sensitivity of the microbial model, searches for the optimal genetic or fluxes design, and finally calculates the robustness of the microbial strains. We are capable to combine the exploration of species, reactions, pathways and knockout parameter spaces with the Pareto optimality principle. RESULTS: Our framework provides also theoretical and practical guidelines for design automation. The statistical cross comparison of our new optimisation procedures, carried out with respect to currently widely used algorithms for bacteria (e.g. Escherichia coli) over different multiple functions, reveals good performances over a variety of biotechnological products. CONTACT: nicosia@dmi.unict.it, pl219@cam.ac.uk.Availability and SUPPLEMENTARY INFORMATION: http://www.dmi.unict.it/nicosia/pathDesign.html.Bioinformatics 10/2012; · 5.47 Impact Factor

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