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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References
Altschul, S.: Gap costs for multiple sequence alignment. Journal of Theoretical Biology 138, 297–309 (1989)
Hirschberg, D.S.: A linear space algorithm for computing common subsequences. Communications of the ACM 18(6), 341–343 (1975)
Kissmann, P.: Externalisierung des Sequenzenalignierungsproblems. Diploma Thesis, University of Dortmund (January 2007)
Korf, R.E., Zhang, W., Thayer, I., Hohwald, H.: Frontier search. Journal of the ACM 52(5), 715–748 (2005)
Niewiadomski, R., Amaral, J.N., Holte, R.C.: Sequential and parallel algorithms for frontier A* with delayed duplicate detection. In: AAAI (2006)
Schroedl, S.: An improved search algorithm for optimal multiple sequence alignment. Journal of Artificial Intelligence Research 23, 587–623 (2005)
Wah, B.W., Shang, Y.: A comparison of a class of IDA* search algorithms. International Journal of Tools with Artificial Intelligence 3(4), 493–523 (1995)
Zhou, R., Hansen, E.: Sparse-memory graph search. In: IJCAI, pp. 1259–1268 (2003)
Zhou, R., Hansen, E.: Sweep A*: Space-efficient heuristic search in partially-ordered graphs. In: ICTAI, pp. 427–434 (2003)
Zhou, R., Hansen, E.: Breadth-first heuristic search. In: ICAPS, pp. 92–100 (2004)
Zhou, R., Hansen, E.: K-Group A* for multiple sequence alignment with quasi-natural gap costs. In: ICTAI, pp. 688–695 (2004)
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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
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