1. BNFO 236 Smith Waterman alignment
Usman Roshan

2. Local alignment Global alignment may not find local similarities
Modification of Needleman-Wunsch yields the Smith-Watermn algorithm for local alignment
Useful in motif detection, database search, short read mapping

3. Local alignment Global alignment initialization:
Local alignment recurrence

4. Local alignment Global alignment recurrence:
Local alignment recurrence

5. Local alignment traceback
Let T(i,j) be the traceback matrices and m and n be length of input sequences.
Global alignment traceback:
Begin from T(m,n) and stop at T(0,0).
Local alignment traceback:
Find i*,j* such that T(i*,j*) is the maximum over all T(i,j).
Begin traceback from T(i*,j*) and stop when
T(i,j) <= 0.