Motivation: In this article, we consider the bicriteria pairwise sequence alignment problem and propose extensions of dynamic programming algorithms for several problem variants with a novel pruning technique that efficiently reduces the number of states to be processed. Moreover, we present a method for the construction of phylogenetic trees based on this bicriteria framework. Two exemplary cases are discussed. Results: Numerical results on a real dataset show that this approach is very fast in practice. The pruning technique saves up to 90% in memory usage and 80% in CPU time. Based on this method, phylogenetic trees are constructed from real-life data. In addition of providing complementary information, some of these trees match those obtained by the Maximum Likelihood method.
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