A Deoxyribonucleic Acid Compression Algorithm Using Auto-Regression and Swarm Intelligence

Abstract

DNA compression challenge has become a major task for many researchers as a result of exponential increase of produced DNA sequences in gene databases; in this research we attempt to solve the DNA compression challenge by developing a lossless compression algorithm. The proposed algorithm works in horizontal mode using a substitutional-statistical technique which is based on Auto Regression modeling (AR), the model parameters are determined using Particle Swarm Optimization (PSO). This algorithm is called Swarm Auto-Regression DNA Compression (SARDNAComp). SARDNAComp aims to reach higher compression ratio which make its application beneficial for both practical and functional aspects due to reduction of storage, retrieval, transmission costs and inferring structure and function of sequences from compression, SARDNAComp is tested on eleven benchmark DNA sequences and compared to current algorithms of DNA compression, the results showed that (SARDNAComp) outperform these algorithms.