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bioRxiv · 10.1101/103101

A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment

Rubio-Largo, A.·Vega-Rodriguez, M. A.
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Abstract

The alignment among three or more nucleotides/amino-acids sequences at the same time is known as Multiple Sequence Alignment (MSA), an NP-hard optimization problem. The time complexity of finding an optimal alignment raises exponentially when the number of sequences to align increases. In this work, we deal with a multiobjective version of the MSA problem where the goal is to simultaneously optimize the accuracy and conservation of the alignment. A parallel version of the Hybrid Multiobjective Memetic Metaheuristics for Multiple Sequence Alignment is proposed. In order to evaluate the parallel performance of our proposal, we have selected a pull of datasets with different number of sequences (up to 1000 sequences) and study its parallel performance against other well-known parallel metaheuristics published in the literature, such as MSAProbs, T-Coffee, Clustal {Omega}, and MAFFT. The comparative study reveals that our parallel aligner is around 25 times faster than the sequential version with 32 cores, obtaining a parallel efficiency around 80%.

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Rubio-Largo, A., Vega-Rodriguez, M. A.. 2017-01-25. A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment. https://doi.org/10.1101/103101

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