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Communication is fundamental to life on earth. All social organisms, from bacteria to humans, use communicative signals to coordinate their behaviors with members of their own and other species. Despite its key role in social organization, many questions r ...
Experimental techniques in molecular biology have led to the production of enormous amounts of data on the dynamics of cellular processes. The availability of time series data characterizing genomic, proteomic and metabolic systems must be complemented wit ...
This article concerns the following question arising in computational evolutionary biology. For a given subclass of phylogenetic networks, what is the maximum value of 0
The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequence ...
In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network to ...
Background: Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present evolutionary approaches to improve the inference of regulatory networks for ...
Although dispersal is recognized as a key issue in several fields of population biology (such as behavioral ecology population genetics metapopulation dynamics or evolutionary modeling) these disciplines focus on different aspects of the concept and often ...
Sequence motifs are of greater biological importance in nucleotide and protein sequences. The conserved occurrence of identical motifs represents the functional significance and helps to classify the biological sequences. In this paper, a new algorithm is ...
Evolutionary robotics is a promising approach to overcoming the limitations and biases of human designers in producing control strategies for autonomous robots. However, most work in evolutionary robotics remains solely concerned with optimizing control st ...
In this paper, we suggest a new approach for reverse engineering gene regulatory networks, which consists of using a reconstruction process that is similar to the evolutionary process that created these networks. The aim is to integrate prior knowledge int ...