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Externalizing the Multiple Sequence Alignment Problem with Affine Gap Costs

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KI 2007: Advances in Artificial Intelligence (KI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4667))

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Abstract

Multiple sequence alignment (MSA) is a problem in computational biology with the goal to discover similarities between DNA or protein sequences. One problem in larger instances is that the search exhausts main memory. This paper applies disk-based heuristic search to solve MSA benchmarks. We extend iterative-deepening dynamic programming, a hybrid of dynamic programming and IDA*, for which optimal alignments with respect to similarity metrics and affine gap cost are computed. We achieve considerable savings of main memory with an acceptable time overhead. By scaling buffer sizes, the space-time trade-off can be adapted to existing resources.

The work is supported by DFG in the projects ED-74/3 and ED-74/4.

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Authors and Affiliations

  1. Computer Science Department, University of Dortmund,  

    Stefan Edelkamp & Peter Kissmann

Authors
  1. Stefan Edelkamp
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  2. Peter Kissmann
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Joachim Hertzberg Michael Beetz Roman Englert

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© 2007 Springer-Verlag Berlin Heidelberg

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Edelkamp, S., Kissmann, P. (2007). Externalizing the Multiple Sequence Alignment Problem with Affine Gap Costs. In: Hertzberg, J., Beetz, M., Englert, R. (eds) KI 2007: Advances in Artificial Intelligence. KI 2007. Lecture Notes in Computer Science(), vol 4667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74565-5_36

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  • DOI: https://doi.org/10.1007/978-3-540-74565-5_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74564-8

  • Online ISBN: 978-3-540-74565-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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