A challenge revisited: An efficient bi-fragmented 16-bit Genpack technique for genetic (DNA&mRNA) compression

While technology keeps growing the world keeps shrinking. Necessity of genome compression is playing a predominant role in the real vogue. Day by day more and more genetic living organism is generated and its accumulation is creating a major problem for processing in centralized and distributed environment. Genome data can be classified into DNA and mRna textures which encoded by four literals of A, C, G and T. Due to the excessive storage of living organism in the public data bases like GenBank and EMBL their size is exponentially growing, for ease of processing the data in the network and storage in the data base genetic compression striving into the world as a major concern. Many classical algorithms are fails to explain genetic sequences due to tandem and non tandem repeats in DNA&mRNA. Some algorithms explained the performance analysis based on tandem repeats in Best, Avg and worst cases but results are not ample. Our proposed technique Genpack uses public 32 bit key for encoding and decoding process. Gen pack will work on both tandem repeats and non tandem repeats and observed that compression is 1.002 bits/characters. It is a finest technique among all existed ones and by using this technique data can be easily managed by substantially reducing its infrastructure in networks, obviously quality of service(Qos) can be reinforced.