Evolutionary and Swarm Intelligence methods for Systems Biology

In many fields of life sciences, mathematical modeling and computational analysis are more and more exploited as complementary tools to experimental laboratory methods [Kitano 2002] . Thanks to this synergy, researchers can nowadays achieve a faster and in-depth understanding of biological systems. However, dynamic mathematical models require a proper parameterization (e.g., the kinetic parameters of reactions) to perform faithful simulations and lead to a better understanding of such systems. Kinetic parameters are often difficult, or even impossible, to measure by means of experimental methodologies. This leads to the problem of Parameter Estimation (PE) [Chou 2009] , that is, the inference of parameters according to some indirect measurement (e.g., experimental time-series of chemical species concentrations).

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