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DNA is a complex molecule that consists of biological information that is passed down from generation to generation. With the evolution over time, there are different kinds of species that evolved from a common ancestor because of the occurrence of DNA sequence rearrangements. DNA sequence similarity analysis is a major challenge since the number of sequences is rapidly increasing in the DNA database. In this research, we based a mathematical method to analyze the similarity of two DNA sequences using Graph Theory. This mathematical method started by modeling a weighted directed graph for each DNA sequence, constructing its adjacency matrix, and converting it to the representative vector for each graph. From these vectors, the similarity was determined by distance measurements such as Euclidean, Cosine, and Correlation. By keeping this method as the based method, we will check whether it is applicable for any DNA fragments in considered genomes and molecular similarity coefficients can be used as distance measurements. We will obtain similarities using the graph spectrum instead of the representative vector. Then we will compare the results from the representative vector and that of the graph spectrum. The modified method is tested by using the mitochondrial DNA of Human, Gorilla, and Orangutan. It gives the same result when the number of nucleotides in DNA fragments is increased.
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