Multiple sequence alignment (MSA) is one of the most useful tools in bioinformatics. MSA plays a key role in protein/RNA structure prediction, phylogenetic analysis or pattern identification among other important bioinformatic applications. However, the growth of sequencing data imposes further difficulties to aligning it with traditional tools. For large-scale alignments with thousands of sequences or even whole genomes, it will be necessary to use and take advantage of high performance computing (HPC). This paper, focused on a consistency-based MSA tool called T-Coffee, presents several innovative solutions; the Balanced Guide Tree, the Optimized Library Method and the Multiple Tree Alignment. The results obtained by the methods presented have demonstrated that it is possible to improve efficiency, scalability and accuracy.
High performance computing techniques have been used for MSA tools in REF .
High Performance computing improvements on bioinformatics consistency-based multiple sequence alignment tools
Parallel Comput.
Parallel Comput.
Computer Science