Phylogenetic networks are models of the evolution of a set of organisms that generalize phylogenetic trees. By allowing the existence of reticulation events (such as recombination, hybridization, or horizontal gene transfer), the model is no longer a tree but a directed acyclic graph (DAG). We consider the problem of finding a phylogenetic network to model a set of sequences of molecular data, using evolutionary algorithms (EAs). To this end, the algorithm has to be adequately designed to handle different constraints regarding the structure of the DAG, and the location of reticulation events. The choice of fitness function is also studied, and several possibilities for this purpose are presented and compared. The experimental evaluation indicates that the EA can satisfactorily recover the underlying evolution model behind the data. A computationally light fitness function seems to provide the best performance. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Trujillo, J. D., & Cotta, C. (2006). An evolutionary approach to the inference of phylogenetic networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4193 LNCS, pp. 332–341). Springer Verlag. https://doi.org/10.1007/11844297_34
Mendeley helps you to discover research relevant for your work.