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Hybrid Genetic Algorithm and Lasso Test Approach for Inferring Well Supported Phylogenetic Trees Based on Subsets of Chloroplastic Core Genes

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9199))

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Abstract

The amount of completely sequenced chloroplast genomes increases rapidly every day, leading to the possibility to build large scale phylogenetic trees of plant species. Considering a subset of close plant species defined according to their chloroplasts, the phylogenetic tree that can be inferred by their core genes is not necessarily well supported, due to the possible occurrence of “problematic” genes (i.e., homoplasy, incomplete lineage sorting, horizontal gene transfers, etc.) which may blur phylogenetic signal. However, a trustworthy phylogenetic tree can still be obtained if the number of problematic genes is low, the problem being to determine the largest subset of core genes that produces the best supported tree. To discard problematic genes and due to the overwhelming number of possible combinations, we propose an hybrid approach that embeds both genetic algorithms and statistical tests. Given a set of organisms, the result is a pipeline of many stages for the production of well supported phylogenetic trees. The proposal has been applied to different cases of plant families, leading to encouraging results for these families.

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References

  1. Alkindy, B., Couchot, J.F., Guyeux, C., Mouly, A., Salomon, M., Bahi, J.M.: Finding the core-genes of chloroplasts. J. Biosci. Biochem. Bioinform. 4(5), 357–364 (2014)

    Google Scholar 

  2. Alkindy, B., Guyeux, C., Couchot, J.-F., Salomon, M., Bahi, J.M.: Gene similarity-based approaches for determining core-genes of chloroplasts. In: 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 71–74. IEEE (2014)

    Google Scholar 

  3. Bhandari, D., Murthy, C., Pal, S.K.: Genetic algorithm with elitist model and its convergence. Int. J. Pattern Recogn. Artif. Intell. 10(06), 731–747 (1996)

    Article  Google Scholar 

  4. Booker, L.B., Goldberg, D.E., Holland, J.H.: Classifier systems and genetic algorithms. Artif. Intell. 40(1), 235–282 (1989)

    Article  Google Scholar 

  5. Edgar, R.C.: Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5), 1792–1797 (2004)

    Article  Google Scholar 

  6. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1993)

    Google Scholar 

  7. Gupta, M., Singh, S.: A novel genetic algorithm based approach for optimization of distance matrix for phylogenetic tree construction. Int. J. Comput. Appl. 52(9), 14–18 (2012)

    MathSciNet  Google Scholar 

  8. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  9. Holland, J.H.: Adaptation in Natural and Artificial Systems, 2nd edn. MIT Press, Cambridge (1992)

    Google Scholar 

  10. Matsuda, H.: Construction of phylogenetic trees from amino acid sequences using a genetic algorithm. In: Proceedings of Genome Informatics Workshop, vol. 6, pp. 19–28 (1995)

    Google Scholar 

  11. Palmer, J.D.: Plastid chromosomes: structure and evolution. Mol. Biol. Plastids 7, 5–53 (1991)

    Article  Google Scholar 

  12. Prebys, E.K.: The genetic algorithm in computer science. MIT Undergrad. J. Math 2007, 165–170 (2007)

    Google Scholar 

  13. Stamatakis, A., Ludwig, T., Meier, H.: Raxml-iii: a fast program for maximum likelihood-based inference of large phylogenetic trees. Bioinformatics 21(4), 456–463 (2005)

    Article  Google Scholar 

  14. Tate, S.I., Yoshihara, I., Yamamori, K., Yasunaga, M.: A parallel hybrid genetic algorithm for multiple protein sequence alignment. In: Proceedings of the World on Congress on Computational Intelligence, vol. 1, pp. 309–314. IEEE (2002)

    Google Scholar 

  15. Tibshirani, R.: Regression shrinkage and selection via the lasso. J. Roy. Stat. Soc. (Ser. B) 58, 267–288 (1996)

    MathSciNet  MATH  Google Scholar 

  16. Wyman, S.K., Jansen, R.K., Boore, J.L.: Automatic annotation of organellar genomes with dogma. Bioinformatics 20(17), 3252–3255 (2004). Oxford Press

    Article  Google Scholar 

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Acknowledgement

Computations have been performed on the supercomputer facilities of the Mésocentre de calcul de Franche-Comté.

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Authors and Affiliations

  1. FEMTO-ST Institute, UMR 6174 CNRS, DISC Computer Science Department, University of Franche-Comté, Besançon, France

    Bassam AlKindy, Christophe Guyeux, Jean-François Couchot, Michel Salomon & Jacques M. Bahi

  2. Laboratory of Evolutionary Botany, University of Neuchâtel, Neuchâtel, Switzerland

    Christian Parisod

  3. Department of Computer Science, University of Mustansiriyah, Baghdad, Iraq

    Bassam AlKindy

Authors
  1. Bassam AlKindy
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  2. Christophe Guyeux
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  3. Jean-François Couchot
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  4. Michel Salomon
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  5. Christian Parisod
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  6. Jacques M. Bahi
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Corresponding author

Correspondence to Bassam AlKindy .

Editor information

Editors and Affiliations

  1. Research Group on Mathematical Linguistics, Rovira i Virgili University, Tarragona, Spain

    Adrian-Horia Dediu

  2. Faculty of Science, National Autonomous University of Mexico - UNAM, Mexico City, Mexico

    Francisco Hernández-Quiroz

  3. Research Group on Mathematical Linguistics, Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  4. Institute for Research in Applied Mathematics and Systems – IIMAS, National Autonomous University of Mexico - UNAM, Mexico City, Mexico

    David A. Rosenblueth

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AlKindy, B., Guyeux, C., Couchot, JF., Salomon, M., Parisod, C., Bahi, J.M. (2015). Hybrid Genetic Algorithm and Lasso Test Approach for Inferring Well Supported Phylogenetic Trees Based on Subsets of Chloroplastic Core Genes. In: Dediu, AH., Hernández-Quiroz, F., Martín-Vide, C., Rosenblueth, D. (eds) Algorithms for Computational Biology. AlCoB 2015. Lecture Notes in Computer Science(), vol 9199. Springer, Cham. https://doi.org/10.1007/978-3-319-21233-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-21233-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21232-6

  • Online ISBN: 978-3-319-21233-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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