Bioinformatics features based DNA Sequence data compression algorithm

被引：0
|
作者：
Ji, Zhen [1 ]
Zhou, Jia-Rui [2 ]
Zhu, Ze-Xuan [1 ]
Wu, Q.H. [3 ]
机构：
[1] College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China
[2] College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, China
[3] Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, United Kingdom
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2011年 / 39卷 / 05期
关键词：
DNA sequences - Data compression - Markov processes - Clustering algorithms - DNA - Benchmarking;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A novel bioinformatics features based DNA Sequence data compression algorithm of BioLZMA is proposed in this paper. In BioLZMA, the DNA sequence data is sliced and reformed into 4 clusters according with biological meanings: the coding sequence cluster, the intron cluster, the RNA cluster and the residual cluster. By employing pointed compression strategies in data pre-processing, the clusters are compressed separately with LZMA algorithm. Experimental results demonstrated the better performance of BioLZMA than original DNA compression algorithms on benchmark sequences. Especially on long DNA sequence with significant bioinformatics features, BioLZMA algorithm can achieve higher compression ratio with little computation time.
引用
收藏
页码：991 / 995
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