In a typical “left-to-right” phylogenetic tree, the vertical or- der 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 in- vestigated 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.

Investigating Populational Evolutionary Algorithms to add Vertical Meaning in Phylogenetic Trees

CERUTTI, FRANCESCO;BERTOLOTTI, Luigi;GIACOBINI, Mario Dante Lucio
2010-01-01

Abstract

In a typical “left-to-right” phylogenetic tree, the vertical or- der 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 in- vestigated 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.
2010
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 8th European Conference EvoBIO 2010
Istanbul, Turkey
April 2010
Proceedings of the 8th European Conference EvoBIO 2010
Springer Verlag
6023
240
248
evolutionary computation; machine learning; data mining; bioinformatics; computational biology
Cerutti, Francesco; Bertolotti, Luigi; Goldberg, T. L.; Giacobini, Mario Dante Lucio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/74123
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