KI 2007: Advances in Artificial Intelligence

Volume 4667 of the series Lecture Notes in Computer Science pp 444-447

Externalizing the Multiple Sequence Alignment Problem with Affine Gap Costs

  • Stefan EdelkampAffiliated withComputer Science Department, University of Dortmund
  • , Peter KissmannAffiliated withComputer Science Department, University of Dortmund

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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.