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IEEE Computer Society Bioinformatics Conference (CSB'03)   p. 326
ANTICLUSTAL: Multiple Sequence Alignment by Antipole Clustering and Linear Approximate 1-Median Computation
C. Di Pietro, Università di Catania
V. Di Pietro, Università di Catania
G. Emmanuele, Università di Catania
A. Ferro, Università di Catania
T. Maugeri, Università di Catania
E. Modica, Università di Catania
G. Pigola, Università di Catania
A. Pulvirenti, Università di Catania
M. Purrello, Università di Catania
M. Ragusa, Università di Catania
M. Scalia, Università di Catania
D. Shasha, New York University
S. Travali, Università di Catania
V. Zimmitti, Università di Catania

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2003.1227333
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Abstract
In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.
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Index Terms- Multiple Sequence Alignment, Clustering, Randomized Tournament Citation:  C. Di Pietro, V. Di Pietro, G. Emmanuele, A. Ferro, T. Maugeri, E. Modica, G. Pigola, A. Pulvirenti, M. Purrello, M. Ragusa, M. Scalia, D. Shasha, S. Travali, V. Zimmitti, "ANTICLUSTAL: Multiple Sequence Alignment by Antipole Clustering and Linear Approximate 1-Median Computation," csb, p. 326,  IEEE Computer Society Bioinformatics Conference (CSB'03),  2003