DNA synthetic sequences generation using multiple competing Markov models

The development and implementation of computational models to represent DNA sequences is a great challenge. Markov models, usually known as finite-context models, have been used for a long time in DNA compression. In a previous work, we have shown that finite-context modelling can also be used for sequence generation. Furthermore, it is known that DNA is better represented by multiple finite-context models. However, the previous generator only allowed a single finite-context model to be used for generating a certain sequence. In this paper, we present results regarding a synthetic DNA generator based on multiple competing finite-context models.