Abstract

Genome sequence compression based on optimized context weighting

Context weighting is an important technology for genome compression. In this study, we discuss the relationship between the weighting of context models and the weighting of the description lengths corresponding to their respective context models. It indicates that weighting of context models is equivalent to the weighting of their description lengths. With these discussions, we present the weights optimization algorithm based on the minimum description length, and suggest implementing the least-square algorithm for the optimization of the weights. The proposed optimization algorithm is used in the compression of bacterial genome sequences. The experiment results indicate that by using the proposed weights optimization method, our context weighting-based genome compression algorithm can achieve better performance than context weighting-based algorithms reported in the literature.

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