Probabilistic regular sticker system and its properties

Sticker system was introduced by Kari in 1998. Sticker system is a model for DNA computing using the recombination behavior of DNA molecules based on the Watson-Crick complementary: starting from the incomplete double stranded sequences and iteratively using sticking operations until a complete double stranded sequence is obtained. It is known that sticker systems with finite sets of axioms and sticker rules generate only regular languages. Hence, different types of restrictions have been considered to increase the computational power of sticker systems. Recently, a variant of restricted sticker systems, called probabilistic sticker systems, has been introduced. In this system, probabilities are initially associated with the axioms, and the probability of a generated string is computed by multiplying the probabilities of all occurrences of the initial strings in the computation of the string. Strings for the language are selected according to some probabilistic requirements. In this paper, we study the properties of probabilistic regular sticker systems. We prove that the probabilistic enhancement increases the computational power of regular sticker systems