An Algorithm Transform DNA Sequences to Improve Accuracy in Similarity Search

Similarity search of DNA sequences is a fundamental problem in the bioinformatics, serving as basis for many other problems. In this, calculation similarity value between most important, with Edit distance (ED) commonly used due to its high accuracy, but slow speed. With advantage transforming original into numerical vector form that retaining unique features based on properties. The processing these transformed data will be much faster, times faster than direct comparison sequence. Additionally, from long sequence, after transformation, it typically has lower storage capacity, making have good compression. challenge this job develop algorithms maintain biological significance while ensuring which also solved. Previous methods often pure mathematical statistics such frequency and matrix transformations construct features. paper, an improved algorithm proposed both significances gene vectors ease improve accuracy sequences. Based experimental results, new improves calculations maintaining performance.