Common Subsequences in Genome Sequences: An Algorithm Using Binary Search Trees

Deoxyribonucleic acid (DNA), plays a crucial role in the field of biology. Identifying similar DNA sequences across species is critical for understanding genomics and evolutionary biology, due to DNA’s role as the universal genetic code. The identification of similar sequences serves many purposes, some of which include the tracing of evolutionary relationships, studying hereditary diseases, and supporting forensic analysis amongst different species. In this paper, we focus on the development of an algorithm that successfully outputs the shared subsequences between two sequences and a specified length. Our primary goal is to successfully and efficiently run this algorithm, that produces quick and reliable results. To achieve this goal, we discuss and highlight the usage of a Binary Search Tree (BST), a data structure, due to its ability to efficiently organize and search data, and its ability to swiftly retrieve data. Providing three inputs, which consist of two sequences and one specified length, the algorithm will successfully output the shared values in both sequences. The outcomes of this research demonstrate the usefulness of algorithms and different data structures in different practical applications, such as advancements in efficient data processing and technology. Ultimately, this research shows the potential and value of computational approaches in addressing real-world challenges related to genetic research.