Genome Compression based on Hilbert Space Filling Curve
Hongyi Guo, Min Chen, Xi Liu, Mengmeng Xie
Available Online June 2015.
- https://doi.org/10.2991/meici-15.2015.294How to use a DOI?
- Genome sequence compression; Hilbert space filling; Context weighting; Description length.
- The genome compression algorithm based on the Hilbert space-filling curve is proposed in this paper. In order to utilize the correlations among the bases in the genome sequence, our algorithm firstly use the Hilbert space filling curve to map the genome sequence into a new 2-D image. Then the image obtained is encoded by the context weighting modeling technology. For context weighting, the values of weights are corresponding to the description length of the context model which is corresponding to their weights respectively. When the receiver obtain the mapping image, the reverse Hilbert space filling matrix is used to help the decoding procedure. The experiments results indicate that the final compression results by our algorithm are better than the results by other similar algorithms, although the useless area which will lead to the reduce of the compression efficiency is resulted in the mapping image by our algorithm.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hongyi Guo AU - Min Chen AU - Xi Liu AU - Mengmeng Xie PY - 2015/06 DA - 2015/06 TI - Genome Compression based on Hilbert Space Filling Curve BT - 2015 International Conference on Management, Education, Information and Control PB - Atlantis Press SP - 1685 EP - 1689 SN - 1951-6851 UR - https://doi.org/10.2991/meici-15.2015.294 DO - https://doi.org/10.2991/meici-15.2015.294 ID - Guo2015/06 ER -