The Smith-Waterman algorithm for local alignment
Like the technique of Needleman
and Wunsch, this is a matrix-based
approach. The Smith-Waterman method has been used as the basis for many subsequent
algorithms. A key feature of the
Smith-Waterman algorithm is that each cell in the matrix defines the end point of a potential alignment,
whose similarity is represented by
the value stored in the cell. The algorithm thus begins by filling the edge elements with 0.0
value. The next step is to populate the
remaining cells in the matrix. This is achieved by evaluating three functions and choosing the
maximum of the three values. Once
the matrix is complete, the highest score is located, and the other elements leading to this
cell are determined using a
back-tracking procedure.