Abstract
The Spliced Alignment Problem is a well-known problem in Bioinformatics with application to the gene prediction task. This problem consists in finding an ordered subset of non-overlapping substrings of a subject sequence g that best fits a target sequence t. In this work we present an approximation algorithm for a variant of the Spliced Alignment Problem, called Multiple Spliced Alignment Problem, that involves more than one target sequence. Under a metric, this algorithm is proved to be a 3-approximation for the problem and its good practical results compare to those obtained by four heuristics already developed for the Multiple Spliced Alignment Problem.
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Mazaro, R.B., de Lima, L.I.S., Adi, S.S. (2014). A 3-Approximation Algorithm for the Multiple Spliced Alignment Problem and Its Application to the Gene Prediction Task. In: Moura, E., Crochemore, M. (eds) String Processing and Information Retrieval. SPIRE 2014. Lecture Notes in Computer Science, vol 8799. Springer, Cham. https://doi.org/10.1007/978-3-319-11918-2_13
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DOI: https://doi.org/10.1007/978-3-319-11918-2_13
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