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Using Secondary Structure Information to Perform Multiple Alignment

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Transactions on Computational Systems Biology III

Part of the book series: Lecture Notes in Computer Science ((TCSB,volume 3737))

Abstract

In this paper an approach devised to perform multiple alignment is described, able to exploit any available secondary structure information. In particular, given the sequences to be aligned, their secondary structure (either available or predicted) is used to perform an initial alignment –to be refined by means of locally-scoped operators entrusted with “rearranging” the primary level. Aimed at evaluating both the performance of the technique and the impact of “true” secondary structure information on the quality of alignments, a suitable algorithm has been implemented and assessed on relevant test cases. Experimental results point out that the proposed solution is particularly effective when used to align low similarity protein sequences.

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Author information

Authors and Affiliations

  1. University of Cagliari, Piazza d’Armi, I-09123, Cagliari, Italy

    Giuliano Armano & Alessandro Orro

  2. ITB-CNR, Via Fratelli Cervi, 93, 20090, Segrate Milano, Italy

    Luciano Milanesi

Authors
  1. Giuliano Armano
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  2. Luciano Milanesi
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  3. Alessandro Orro
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Editor information

Editors and Affiliations

  1. Centre for Computational and Systems Biology, The Microsoft Research - University of Trento, Piazza Manci, 17, 38050, Povo (TN), Italy

    Corrado Priami

  2. Dipartimento di Matematica e Informatica, Università di Camerino, I-62032, Camerino, Italy

    Emanuela Merelli

  3. DEIS, Università di Bologna, Via Venezia 52, 47023, Cesena, Italy

    Pablo Gonzalez

  4. Alma Mater Studiorum Università di Bologna a Cesena,, via Venezia 52, 47023, Cesena, Italy

    Andrea Omicini

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© 2005 Springer-Verlag Berlin Heidelberg

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Armano, G., Milanesi, L., Orro, A. (2005). Using Secondary Structure Information to Perform Multiple Alignment. In: Priami, C., Merelli, E., Gonzalez, P., Omicini, A. (eds) Transactions on Computational Systems Biology III. Lecture Notes in Computer Science(), vol 3737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599128_6

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  • DOI: https://doi.org/10.1007/11599128_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30883-6

  • Online ISBN: 978-3-540-31446-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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