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Neural Computing and Applications

, Volume 19, Issue 8, pp 1103–1132 | Cite as

An immune-inspired multi-objective approach to the reconstruction of phylogenetic trees

  • Guilherme P. Coelho
  • Ana Estela A. da Silva
  • Fernando J. Von Zuben
AIS

Abstract

This work presents the application of the omni-aiNet algorithm—an immune-inspired algorithm originally developed to solve single and multi-objective optimization problems—to the reconstruction of phylogenetic trees. The main goal here is to automatically evolve a population of phylogenetic unrooted trees, possibly with distinct topologies, by minimizing at the same time two optimization criteria: the minimum evolution and the mean-squared error. This proposal generates, in a single run, a set of non-dominated solutions that represent the trade-offs of the two conflicting objectives, and gives the user the possibility of having distinct explanations for the differences observed at the terminal nodes of the trees. A series of experimental results is also reported in this work, in order to illustrate the effectiveness of the proposal and its capability to overcome the restrictive feedback provided by the application of well-known algorithms for phylogenetic reconstruction, such as the Neighbor Joining. Besides, the methodology presented in this work is compared to the popular NSGA-II algorithm, also modified to solve phylogenetic reconstruction problems.

Keywords

Phylogenetic trees Multi-objective optimization Artificial immune systems Neighbor joining 

Notes

Acknowledgments

The authors would like to thank Prof. Sérgio Furtado dos Reis for providing the distance matrix of the Trichomys apereoides problem, and CAPES and CNPq for the financial support.

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Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Guilherme P. Coelho
    • 1
  • Ana Estela A. da Silva
    • 2
  • Fernando J. Von Zuben
    • 1
  1. 1.Laboratory of Bioinformatics and Bioinspired Computing (LBiC), Department of Computer Engineering and Industrial Automation (DCA)School of Electrical and Computer Engineering (FEEC), University of Campinas (Unicamp)CampinasBrazil
  2. 2.School of Mathematical and Nature SciencesMethodist University of Piracicaba (UNIMEP)PiracicabaBrazil

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