Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the first mutation--selection scheme to the refined (¯,)--ES including

principles of populations. These algorithms process a population of chromo-somes, which represent search space solutions, with three operations: selection, crossover and mutation. Under its initial formulation, the search space solutions are coded using the binary alphabet. However, the good properties

-forward views based on inhibitory contour interactions. From the time a stimulus first enters the eye to the time a percept emerges into consciousness, the initial stimulus has been coded at several levels in the visual system. One of the main goals in studying visual information processing is to specify

in disease. The central theme in this paper is the Boolean formalism as a building block for modeling complex, large-scale, and dynamical networks of genetic interactions. We discuss the goals of modeling genetic networks as well as the data requirements. The Boolean formalism is justified from several

enzyme in such a pathway did not lead to the desired effect We know that the structure of complex genetic and biochemical networks lies hidden in the sequence information of our DNA but it is far from trivial to predict gene expression from the sequence code alone. The current availability of microarray

de nationalité suisse et originaire de Zurich (ZH) et Lucerne (LU) acceptée sur proposition du jury:

When the inherent redundancy of the genetic code was discovered, scientists were rightly puzzled by the role of synonymous mutations 1 . The central dogma of molecular biology suggests that synonymous mutations -those that do not alter the encoded amino acid -will have no effect on the resulting

, the model sheds light on the evolutionary time-scales. By studying the relaxation of the correlation function between consecutive mutations at a given position in proteins, we observe separation of the evolutionary time-scales: at short time intervals families of proteins with similar sequences

A maximum likelihood approach was used to estimate the synonymous and nonsynonymous substitution rates in 48 nuclear genes from primates, artiodactyls, and rodents. A codon-substitution model was assumed, which accounts for the genetic code structure, transition/transversion bias, and base

In the framework of the crystal basis model of the genetic code, where each codon is assigned to an irreducible representation of Uq→0(sl(2) ⊕sl(2)), single base mutation matrices are introduced. The strength of the mutation is assumed to depend on the “distance ” between the codons. Preliminary