  DNA sequence alignment is important today as it is usually the first step in
finding gene mutation, evolutionary similarities, protein structure, drug
development and cancer treatment. Covid-19 is one recent example. There are
many sequencing algorithms developed over the past decades but the sequence
alignment using expert systems is quite new. To find DNA sequence alignment,
dynamic programming was used initially. Later faster algorithms used small DNA
sequence length of fixed size to find regions of similarity, and then build the
final alignment using these regions. Such systems were not sensitive but were
fast. To improve the sensitivity, we propose a new algorithm which is based on
finding maximal matches between two sequences, find seeds between them, employ
rules to find more seeds of varying length, and then employ a new stitching
algorithm, and weighted seeds to solve the problem
