  Genetic information is encoded in a linear sequence of nucleotides,
represented by letters ranging from thousands to billions. Mutations refer to
changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is
vital in all areas of biology and medicine. Careful monitoring of
virulence-enhancing mutations is essential. However, an enormous amount of
classical computing power is required to analyze genetic sequences of this
size. Inspired by human perception of vision and pixel representation of images
on quantum computers, we leverage these techniques to implement a pairwise
sequence analysis. The methodology has a potential advantage over classical
approaches and can be further applied to identify mutations and other
modifications in genetic sequences. We present a method to display and analyze
the similarity between two genome sequences on a quantum computer where a
similarity score is calculated to determine the similarity between nucleotides.
