Efficient Clustering of Genetic Entities

The paper proposes a novel application of a highly efficient method for comparing symbol sequences based on convolution. The technique utilizes Fast Fourier Transform (FFT) to compare long symbol sequences achieving practical results using commodity PC hardware. While the main focus is on bioinformatics, the proposed approach is general and can work beyond genetic sequences. One of the main advantages of the proposed method is the robustness to insertion/deletion. Also, unlike standard alignment algorithms, the proposed method is parameter-free. The paper shows that the FFT-based comparison allows for efficient clustering of long sequences in bioinformatics as a practical application. Exploration of coronaviruses offers an illustration of the proposed clustering techniques.