Title :
K-group A* for multiple sequence alignment with quasi-natural gap costs
Author :
Zhou, Rong ; Hansen, Eric A.
Author_Institution :
Dept. of Comput. Sci. & Eng., Mississippi State Univ., MS, USA
Abstract :
Alignment of multiple protein or DNA sequences is an important problem in bioinformatics. Previous work has shown that the A* search algorithm can find optimal alignments for up to several sequences, and that a K-group generalization of A* can find approximate alignments for much larger numbers of sequences [T. Ikeda et al. (1999)]. In this paper, we describe the first implementation of K-group A* that uses quasinatural gap costs, the cost model used in practice by biologists. We also introduce a new method for computing gap-opening costs in profile alignment. Our results show that K-group A* can efficiently find optimal or close-to-optimal alignments for small groups of sequences, and, for large numbers of sequences, it can find higher-quality alignments than the widely-used CLUSTAL family of approximate alignment tools. This demonstrates the benefits of A* in aligning large numbers of sequences, as typically compared by biologists, and suggests that K-group A* could become a practical tool for multiple sequence alignment.
Keywords :
DNA; biology computing; computational complexity; generalisation (artificial intelligence); proteins; search problems; sequences; A* search algorithm; DNA sequences; K-group generalization; bioinformatics; multiple protein; multiple sequence alignment; quasinatural gap costs; Bioinformatics; Biological system modeling; Computer science; Costs; DNA; Dynamic programming; Iterative algorithms; Protein engineering; Sequences; State-space methods;
Conference_Titel :
Tools with Artificial Intelligence, 2004. ICTAI 2004. 16th IEEE International Conference on
Print_ISBN :
0-7695-2236-X
DOI :
10.1109/ICTAI.2004.77