Читать книгу Bioinformatics - Группа авторов - Страница 46

The methods used to assess similarity (and, in turn, infer homology) can be grouped into two types: global sequence alignment and local sequence alignment. Global sequence alignment methods take two sequences and try to come up with the best alignment of the two sequences across their entire length. In general, global sequence alignment methods are most applicable to highly similar sequences of approximately the same length. Although these methods can be applied to any two sequences, as the degree of sequence similarity declines, they will tend to miss important biological relationships between sequences that may not be apparent when considering the sequences in their entirety.

Most biologists instead depend on the second class of alignment algorithm – local sequence alignments. In these methods, the sequence comparison is intended to find the most similar regions within the two sequences being aligned, rather than finding (or forcing) an alignment over the entire length of the two sequences being compared. As such, and by focusing on subsequences of high similarity that are more easily alignable, determining putative biological relationships between the two sequences being compared becomes a much easier proposition. This makes local alignment methods one of the approaches of choice for biological discovery. Often times, these methods will return more than one result for the two sequences being compared, as there may be more than one domain or subsequence common to the sequences being analyzed. Local sequence alignment methods are best for sequences that share some degree of similarity or for sequences of different lengths, and the ensuing discussion will focus mostly on these methods.