Background: Most existing methods for comparing and analyzing DNA sequences use
multiple sequence alignment (MSA) algorithms. However, the computation time required for MSA is
usually very long and makes it impossible to analyze a large group of long DNA sequences.
Objective: Here we propose a novel computational method to quickly characterize and compare DNA
Method: We construct a new 2-dimensional (2D) graphical representation of DNA sequences based on
the mathematical concept of joint probability. A dinucleotide is assigned by the product of the signed
probability of the two nucleotides, which is totally independent of the choice of the species studied.
Results: We perform similarity/dissimilarity analyses among three real DNA data sets, the first exon of
the beta-globin gene of eleven animal species, ribulose bisphosphate carboxylase small chain (rbcS)
gene of eleven species of flowering plants, and mitochondrial genome sequences of eleven mammal
Conclusion: Our results coincide with existing biological analyses in the literature. We also compare
our approach with MSA algorithm, which is much quicker and more effective.