A novel lossless encoding algorithm for data compression–genomics data as an exemplar
Data compression is a challenging and increasingly important problem. As the amount of data generated daily continues to increase, efficient transmission and storage have never been more critical. In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and ass...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Bioinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2024.1489704/full |
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| author | Anas Al-okaily Abdelghani Tbakhi |
| author_facet | Anas Al-okaily Abdelghani Tbakhi |
| author_sort | Anas Al-okaily |
| collection | DOAJ |
| description | Data compression is a challenging and increasingly important problem. As the amount of data generated daily continues to increase, efficient transmission and storage have never been more critical. In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. The proposed algorithm follows a divide-and-conquer approach by scanning the whole genome, classifying subsequences based on similarities in their content, and binning similar subsequences together. The data is then compressed into each bin independently. This approach is different than the currently known approaches: entropy, dictionary, predictive, or transform-based methods. Proof-of-concept performance was evaluated using a benchmark dataset with seventeen genomes ranging in size from kilobytes to gigabytes. The results showed a considerable improvement in the compression of each genome, preserving several megabytes compared to state-of-the-art tools. Moreover, the algorithm can be applied to the compression of other data types include mainly text, numbers, images, audio, and video which are being generated daily and unprecedentedly in massive volumes. |
| format | Article |
| id | doaj-art-3c58369ff8fc4259bdd5d3a4439859ee |
| institution | Kabale University |
| issn | 2673-7647 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj-art-3c58369ff8fc4259bdd5d3a4439859ee2025-01-23T06:56:26ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472025-01-01410.3389/fbinf.2024.14897041489704A novel lossless encoding algorithm for data compression–genomics data as an exemplarAnas Al-okaily0Abdelghani Tbakhi1Department of Cell Therapy and Applied Genomics, King Hussein Cancer Center, Amman, JordanDepartment of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, CanadaData compression is a challenging and increasingly important problem. As the amount of data generated daily continues to increase, efficient transmission and storage have never been more critical. In this study, a novel encoding algorithm is proposed, motivated by the compression of DNA data and associated characteristics. The proposed algorithm follows a divide-and-conquer approach by scanning the whole genome, classifying subsequences based on similarities in their content, and binning similar subsequences together. The data is then compressed into each bin independently. This approach is different than the currently known approaches: entropy, dictionary, predictive, or transform-based methods. Proof-of-concept performance was evaluated using a benchmark dataset with seventeen genomes ranging in size from kilobytes to gigabytes. The results showed a considerable improvement in the compression of each genome, preserving several megabytes compared to state-of-the-art tools. Moreover, the algorithm can be applied to the compression of other data types include mainly text, numbers, images, audio, and video which are being generated daily and unprecedentedly in massive volumes.https://www.frontiersin.org/articles/10.3389/fbinf.2024.1489704/fullcompressionHuffman encodingLZgenomicsBWT |
| spellingShingle | Anas Al-okaily Abdelghani Tbakhi A novel lossless encoding algorithm for data compression–genomics data as an exemplar Frontiers in Bioinformatics compression Huffman encoding LZ genomics BWT |
| title | A novel lossless encoding algorithm for data compression–genomics data as an exemplar |
| title_full | A novel lossless encoding algorithm for data compression–genomics data as an exemplar |
| title_fullStr | A novel lossless encoding algorithm for data compression–genomics data as an exemplar |
| title_full_unstemmed | A novel lossless encoding algorithm for data compression–genomics data as an exemplar |
| title_short | A novel lossless encoding algorithm for data compression–genomics data as an exemplar |
| title_sort | novel lossless encoding algorithm for data compression genomics data as an exemplar |
| topic | compression Huffman encoding LZ genomics BWT |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2024.1489704/full |
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