RT Journal Article
SR Electronic
T1 A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 103101
DO 10.1101/103101
A1 Álvaro Rubio-Largo
A1 Leonardo Vanneschi
A1 Mauro Castelli
A1 Miguel A. Vega-Rodríguez
YR 2017
UL http://biorxiv.org/content/early/2017/12/01/103101.abstract
AB 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 Ω, 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%.