Multiple Sequence alignment (MSA) is a generalization of Pairwise Sequence Alignment to multiple sequences. Thus, instead of aligning two sequences, the objective in MSA is to align k sequences simultaneously; such an overall function is optimized. The motivation behind doing an MSA is that it allows us to extract consensus evident in a widely diverse set of sequences. The similarities we observe across a wider range of sequences can help us better understand the evolutionary history of sequences and help infer a functional relationship amongst a group of biological sequences. Particularly for protein sequences, MSA can provide insight into the secondary/tertiary structure of proteins and discover critical consensus motifs and common blocks representative of protein domains or functional units. Generally, however, before performing the MSA step, typically we already know that the set of sequences being aligned are related, and our objective is to discover those regions and the strength of relatedness.

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Multiple Sequence Alignment

  • Gautam B. Singh

摘要

Multiple Sequence alignment (MSA) is a generalization of Pairwise Sequence Alignment to multiple sequences. Thus, instead of aligning two sequences, the objective in MSA is to align k sequences simultaneously; such an overall function is optimized. The motivation behind doing an MSA is that it allows us to extract consensus evident in a widely diverse set of sequences. The similarities we observe across a wider range of sequences can help us better understand the evolutionary history of sequences and help infer a functional relationship amongst a group of biological sequences. Particularly for protein sequences, MSA can provide insight into the secondary/tertiary structure of proteins and discover critical consensus motifs and common blocks representative of protein domains or functional units. Generally, however, before performing the MSA step, typically we already know that the set of sequences being aligned are related, and our objective is to discover those regions and the strength of relatedness.