Abstract:
Local sequence alignment is widely used to
discover structural and hence, functional
similarities between biological sequences. Sequence
database alignment is among the most important
and challenging tasks in bioinformatics. This paper
presents a parallel algorithm that finds all
occurrences of a pattern string in a subject string in
O(log n) time, where n is the length of the subject
string. The number of processors employed is of the
order of the product of the two string lengths. It also
presents advanced computer architectures that
utilize parallelism via multiple processing units.
While parallel computing, in the form of internally
linked processors, was the main form of parallelism,
advances in computer networks has created a new
type of parallelism in the form of networked
autonomous computers. . The right choice of
sequence alignment algorithm is that of Smith-
Waterman. To get high quality results in a short
time is to use parallel processing.
