
It is often a necessity to compare some sequences to find out how similar they are. There are many similarity measures that can be used, e.g., longest common subsequence, edit distance, sequence alignment. Recently a merged longest common subsequence (MergedLCS) problem was formulated with applications in bioinformatics. We propose the bit-parallel algorithms for the MergedLCS problem and evaluate them in practice showing that they are usually tens times faster than the already published methods.
sequence comparison, bit-parallelism, Dynamic programming, Algorithms on strings, merged longest common subsequence
sequence comparison, bit-parallelism, Dynamic programming, Algorithms on strings, merged longest common subsequence
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