Quoc-Nam Tran and Mike Wallinga
We review 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.
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