基于加权Context建模的DNA序列压缩算法

A Genome Sequence Compression Algorithm Based on the Weighted Context Modeling

给出一种基于自适应Context加权的细菌DNA序列压缩算法.不同阶数的Context模型用于描述碱基符号间的关联程度.通过加权的方式将各阶模型进行组合,构建用于驱动算术编码器的条件概率分布.各阶模型对应权值由其相应自适应码长决定.在编码过程中,权值能够根据各阶模型获得的统计计数值自适应更新.实验结果表明,该方法能够获得比其他加权Context建模基因组序列压缩算法更好的压缩效率.

A bacteria genome compression algorithm based on the adaptive weighted context model is present. The context model with different order is used to describe the relation degree of basic group code. The context models are combined by weighting to constitute the conditional probability distribution to drive arithmetic coder and the values of these weights are determined by the corresponding adaptive code length. In the coding process,the values of these weights are adaptively updated according to the statistic count value acquired by the context model. The experimental results indicate that the algorithm presented could produce better compression result than the results by other algorithms.