One of the main challenges facing biology today is the understanding of the joint action of genes, proteins and RNA molecules, interwoven in intricate interdependencies commonly known as genetic networks. To this end, several mathematical approaches have been introduced to date. In addition to...

The activity of the cell is often coordinated by the organisation of proteins into regulatory circuits that share a common function. Genome-wide expression profiles might contain important information on these circuits. Current approaches for the analysis of gene expression data include...

We investigate the adaptation of random boolean networks that are a model for regulatory gene networks. The model considers a general genetic algorithm and a fitness function that takes into account the full network dynamical behavior. We propose a mathematical function to quantify the...

In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games...

Random Boolean networks have been proposed as discrete models of genetic networks. Depending on the values of their control parameters, these networks fall by themselves in order or disorder phases. These networks are autonomous systems: no external inputs are considered. Nevertheless, in the...

A new order parameter approximation to random boolean networks (RBN) is introduced, based on the concept of Boolean derivative. A statistical argument involving an annealed approximation is used, allowing to measure the order parameter in terms of the statistical properties of a random matrix....

Two-layer feedforward neural network was used in this work to forecast chaotic time series with very promising results, especially for the Lorenz system, as in comparison to others that had been previously published elsewhere. It was observed that the architecture m:2m:m:1, where m is the...

The temperature factors series of protein backbone atoms resulting from the X-ray diffraction analysis of crystal data were analyzed by fast Fourier transform, detrended fluctuation analysis (DFA) and correlation dimension. The spectral analysis of 50 randomly selected proteins revealed the...