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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 93))

Abstract

The workflow model of description and execution of complex tasks can be of great use to design and parallelize scientific experiments, though it remains a scarcely studied area in its application to phylogenetic analysis. In order to remedy this situation, we study and identify sources of parallel tasks in the main reconstruction stages as well as in other indispensable problems on which it depends: model selection and sequence alignment. Finally, we present a general-purpose implementation for use in cluster environments and examine the performance of our method through application to very large sets of whole mitochondrial genomes, by which problems of biological interest can be solved with new-found efficiency and accuracy.

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References

  1. Álvarez, J.: Análisis teórico-práctico de métodos de inferencia filogenética basados en selección de modelos y métodos de superárboles. Master’s thesis, Zaragoza (2010)

    Google Scholar 

  2. Bininda-Emonds, O.R.P., Gittleman, J.L., Steel, M.A.: The (super)tree of life: procedures, problems and prospects. Annu. Rev. Ecol. Syst. 33, 265–289 (2002)

    Article  Google Scholar 

  3. Blanco, R., Mayordomo, E.: ZARAMIT: A system for the evolutionary study of human mitochondrial DNA. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, pp. 1139–1142. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  4. Blanco, R., Mayordomo, E., Montes, E., Mayo, R., Alberto, A.: Scalable phylogenetics through input preprocessing. In: Rocha, M.P., Riverola, F.F., Shatkay, H., Corchado, J.M. (eds.) IWPACBB 2010. Advances in Intelligent and Soft Computing, vol. 74, pp. 123–130. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  5. Bowers, S., McPhillips, T., Riddle, S., Anand, M.K., Ludäscher, B.: Kepler/pPOD: Scientific workflow and provenance support for assembling the tree of life. In: Freire, J., Koop, D., Moreau, L. (eds.) IPAW 2008. LNCS, vol. 5272, pp. 70–77. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Couvares, P., Kosar, T., Roy, A., Weber, J., Wenger, K.: Workflow management in Condor. In: Taylor, I.J., Deelman, E., Gannon, D.B., Shields, M. (eds.) Workflows for e-Science, pp. 357–375. Springer, Heidelberg (2006)

    Google Scholar 

  7. Degnan, J.H., Rosenberg, N.A.: Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol. Evol. 24, 332–340 (2009)

    Article  Google Scholar 

  8. Georgakopoulos, D., Hornick, M., Sheth, A.: An overview of workflow management: from process modeling to workflow automation infrastructure. Distrib. Parallel Dat. 3, 119–153 (1995)

    Article  Google Scholar 

  9. Holder, M.T., Lewis, P.O.: Phylogeny estimation: traditional and Bayesian approaches. Nat. Rev. Genet. 4, 275–284 (2003)

    Article  Google Scholar 

  10. Oinn, T., Addis, M., Ferris, J., Marvin, D., Senger, M., Greenwood, M., Carver, T., Glover, K., Pocock, M.R., Wipat, A., Li, P.: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20, 3045–3054 (2004)

    Article  Google Scholar 

  11. Olsen, G.J., Matsuda, H., Hagstrom, R., Overbeek, R.: fastDNAml: a tool for construction of phylogenetic trees of DNA sequences using maximum likelihood. Comput. Appl. Biosci. 10, 41–48 (1994)

    Google Scholar 

  12. Posada, D.: jModelTest: phylogenetic model averaging. Mol. Biol. Evol. 25, 1253–1256 (2008)

    Article  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, 456–463 (2005)

    Article  Google Scholar 

  14. Sullivan, J., Joyce, P.: Model selection in phylogenetics. Annu. Rev. Ecol. Evol. Syst. 36, 445–466 (2005)

    Article  Google Scholar 

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Álvarez, J., Blanco, R., Mayordomo, E. (2011). Workflows with Model Selection: A Multilocus Approach to Phylogenetic Analysis. In: Rocha, M.P., Rodríguez, J.M.C., Fdez-Riverola, F., Valencia, A. (eds) 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011). Advances in Intelligent and Soft Computing, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19914-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-19914-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19913-4

  • Online ISBN: 978-3-642-19914-1

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