Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer

Genome Sequence compression algorithm based on the Distributed source coding

Authors
Jing-Jing Shao
Corresponding Author
Jing-Jing Shao
Available Online June 2016.
DOI
10.2991/mmebc-16.2016.363How to use a DOI?
Keywords
Distributed source coding; Genome sequence compression; Side information; Context weighting; Hilbert spacing filling
Abstract

The genome sequence compression algorithm based on the distributed source coding technology purely is proposed in this paper. In order to enhance the compression efficiency, the genome sequence is mapped into two binary sources and then they are transmitted into two bilevel images. After initialization, the distributed source coding based on LDPC is constructed for compressing these two sequences. To compress the side information, the optimized context weighting is suggested. The experiments results indicate that the coding efficiency is better than results from any other compression algorithms for microbial genome sequence compression.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/mmebc-16.2016.363
ISSN
2352-5401
DOI
10.2991/mmebc-16.2016.363How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jing-Jing Shao
PY  - 2016/06
DA  - 2016/06
TI  - Genome Sequence compression algorithm based on the Distributed source coding
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 1795
EP  - 1799
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.363
DO  - 10.2991/mmebc-16.2016.363
ID  - Shao2016/06
ER  -