Abstract
A formalization of the multiple sequence alignment problem that emphasizes the problem's evolutionary aspect is the Generalized Tree Alignment Problem. Given a set of sequences, this formalization asks for a phylogenetic tree and ancestral sequences such that the implied amount of change necessary to explain the given data is minimal. The problem is computationally hard and we present a heuristic algorithm for it. Our procedure mimicks agglomerative clustering techniques as used for phylogenetic trees while at the same time aligning the sequences using the data structure of sequence graphs. The approach achieves good results in terns of the underlying scoring function. It produces biologically meaningful answers which in this paper we will demonstrate on a set of Alu repeats.
Work supported by DFG grant Vi-160/1
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© 1997 Springer-Verlag Berlin Heidelberg
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Schwikowski, B., Vingron, M. (1997). A clustering approach to Generalized Tree Alignment with application to Alu repeats. In: Hofestädt, R., Lengauer, T., Löffler, M., Schomburg, D. (eds) Bioinformatics. GCB 1996. Lecture Notes in Computer Science, vol 1278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033210
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DOI: https://doi.org/10.1007/BFb0033210
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