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Improving Phylogenetic Tree Interpretability by Means of Evolutionary Algorithms

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Book cover Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBIO 2012)

Abstract

A recent research article, entitled Taxon ordering in phylogenetic trees: a workbench test presented the application of an evolutionary algorithm to order taxa in a phylogenetic tree, according to a given distance matrix. In previous articles, the authors introduced the first approaches to study the influence of algorithm parameters on the efficacy of finding the tree with the shortest distance among taxa, based on genetic distances. In the considered work, the authors tested the algorithm using both genetic and geographic distances, and a combination of the two, on three phylogenetic trees of different viruses. The results were interesting, especially when applying geographic distances, allowing a new reading direction, orthogonal to the classical root-to-taxa one.

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References

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© 2012 Springer-Verlag Berlin Heidelberg

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Cerutti, F., Bertolotti, L., Goldberg, T.L., Giacobini, M. (2012). Improving Phylogenetic Tree Interpretability by Means of Evolutionary Algorithms. In: Giacobini, M., Vanneschi, L., Bush, W.S. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2012. Lecture Notes in Computer Science, vol 7246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29066-4_23

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  • DOI: https://doi.org/10.1007/978-3-642-29066-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29065-7

  • Online ISBN: 978-3-642-29066-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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