Abstract
In a typical “left-to-right” phylogenetic tree, the vertical order of taxa is meaningless, and the degree of similarity between taxa is only reflected by the branch path between them. We applied an Evolutionary Algorithm (EA) to improve the graphical representation of phylogenies, adding interpretability to the vertical order of taxa. We investigated the influence of different populations in the heuristic method to evaluate their influence on a (λ + μ)-EA. In our example, the order of taxa linked to polytomic nodes is optimized using data from genetic distance matrices. However the vertical order of taxa on a phylogenetic tree can also be used to represent non-genetic features of interest.
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Cerutti, F., Bertolotti, L., Goldberg, T.L., Giacobini, M. (2010). Investigating Populational Evolutionary Algorithms to Add Vertical Meaning in Phylogenetic Trees. In: Pizzuti, C., Ritchie, M.D., Giacobini, M. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2010. Lecture Notes in Computer Science, vol 6023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12211-8_21
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DOI: https://doi.org/10.1007/978-3-642-12211-8_21
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