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

Aly, Walid Mohamed; Yousif, Basheer; Zohdy, Bassem S. M.

doi:10.3844/jcssp.2013.690.698

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…Many file formats are used to store the genomic data such as FASTA, FASTQ, BAM/SAM and VCF/BCF [7][8][9][10][11][12][13][14][15]. In these file formats, in addition to the raw genomic or protein sequences, other information, such as in FASTQ file identifiers and quality scores are added.…”

Section: Introductionmentioning

confidence: 99%

“…In June 2019, approximately 329,835,282,370 bases were generated [18]. All of these data are stored in special databases, which have been developed by the scientific community such as the 1000 Genomes Project [6], the International Cancer Genome Project [19] and the ENCODE project [12,17,20]. This advancement has caused the production of a vast amount of redundant data at a much higher rate than the older technologies, which will increase in the future and may go beyond the limit of storage and bandwidth capacity [3][4][5].…”

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confidence: 99%

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A New Lossless DNA Compression Algorithm Based on A Single-Block Encoding Scheme

2020

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With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Therefore, to overcome these challenges, compression has become necessary. In this paper, we describe a new reference-free DNA compressor abbreviated as DNAC-SBE. DNAC-SBE is a lossless hybrid compressor that consists of three phases. First, starting from the largest base (Bi), the positions of each Bi are replaced with ones and the positions of other bases that have smaller frequencies than Bi are replaced with zeros. Second, to encode the generated streams, we propose a new single-block encoding scheme (SEB) based on the exploitation of the position of neighboring bits within the block using two different techniques. Finally, the proposed algorithm dynamically assigns the shorter length code to each block. Results show that DNAC-SBE outperforms state-of-the-art compressors and proves its efficiency in terms of special conditions imposed on compressed data, storage space and data transfer rate regardless of the file format or the size of the data.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

A New Lossless DNA Compression Algorithm Based on A Single-Block Encoding Scheme

2020

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“…So, these facts conclude that DNA sequences should be compressed. Human DNA almost has 3 billion bases and among then more than 99% are the same in all human [8], [9]. Data compression reveals certain theoretical ideas such as entropy, mutual information and complexity between sequences of different genomes.…”

Section: Introductionmentioning

confidence: 99%

SBVRLDNAComp:An Effective DNA Sequence Compression Algorithm

Roy¹,

Bhagot²,

Sharma³

et al. 2015

IJCSA

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There are plenty specific types of data which are needed to compress for easy storage and to reduce overall retrieval times. Moreover, compressed sequence can be used to understand similarities between biological sequences. DNA data compression challenge has become a major task for many researchers for the last few years as a result of exponential increase of produced sequences in gene databases. In this research paper we have attempt to develop an algorithm by self-reference bases; namely Single Base Variable Repeat Length DNA Compression (SBVRLDNAComp). There are a number of reference based compression methods but they are not satisfactory for forthcoming new species. SBVRLDNAComp is an optimal solution of the result obtained from small to long, uniform identical and non-identical string of nucleotides checked in four different ways. Both exact repetitive and non-repetitive bases are compressed by SBVRLDNAComp. The sound part of it is without any reference database SBVRLDNAComp achieves 1.70 to 1.73 compression ratio α after testing on ten benchmark DNA sequences. The compressed file can be further compressed with standard tools (such as WinZip or WinRar) but even without this SBVRLDNAComp outperforms many standard DNA compression algorithms.

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“…A particle updates its velocity and position based on its inertia, own experience and gained knowledge from other particles in the swarm, aiming to find the optimal solution of the problem [17].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules

Darwish¹,

Mohamed²,

Zohdy³

2016

ijarai

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

Cited by 4 publications

References 23 publications

A New Lossless DNA Compression Algorithm Based on A Single-Block Encoding Scheme

A New Lossless DNA Compression Algorithm Based on A Single-Block Encoding Scheme

SBVRLDNAComp:An Effective DNA Sequence Compression Algorithm

Applying Swarm Optimization Techniques to Calculate Execution Time for Software Modules

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