The organization, regulation and dynamical responses of biological systems are in many
cases too complex to allow intuitive predictions and require the support of mathematical …

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools
that facilitate the analysis of dynamic biological systems. This paper depicts major …

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter
optimization algorithms in current use. DE operates through similar computational steps as …

Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference
of positions between individuals to perturb base vectors and thus generate new mutant …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

The term 'Memetic Algorithms'[74](MAs) was introduced in the late 80s to denote a family of
metaheuristics that have as central theme the hybridization of different algorithmic …

Existing differential evolution (DE) algorithms often face two challenges. The first is that the
optimization performance is significantly affected by the ad hoc configurations of operators …

Designing and conducting experiments are routine practices for modern biologists. The real
challenge, especially in the post-genome era, usually comes not from acquiring data, but …

This paper gives a comprehensive review of the application of metaheuristics to optimization
problems in systems biology, mainly focusing on the parameter estimation problem (also …

Memetic algorithms are optimization techniques based on the synergistic combination of
ideas taken from different algorithmic solvers, such as population-based search (as in …