A Novel Method for Multiple Sequence Alignment Using Morphing Techniques

We present a novel computational method for Multiple Sequence Alignment (MSA), a fundamental problem in computational biology. In contrast to other known approaches, our method searches for an optimal alignment - structurally and evolutionarily by inserting or deleting gaps from a set of initial candidates in an efficient manner. Our method called a Universal Partitioning Search (UPS) approach for MSA uses graphical morphism to guarantee that the scores of the alignment candidates are always improved after each particle swarm optimization iteration. We compare our novel method with previous known methods and report our experimental results using BAliBASE test suites. Our initial results showed that the multiple sequence alignments found by our software, which was implemented in Maple and C/Java, are better in some cases or comparable with current state-of-the-art software.