The generative capacity of probabilistic splicing systems

The concept of probabilistic splicing system was introduced as a model for stochastic processes using DNA computing techniques. In this paper we introduce splicing systems endowed with different continuous and discrete probabilistic distributions and call them as probabilistic splicing systems. We s...

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Bibliographic Details
Main Authors: Selvarajoo, Mathuri, Turaev, Sherzod, Fong, Wan Heng, Sarmin, Nor Haniza
Format: Article
Language:English
Published: Natural Publishing 2015
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Online Access:http://irep.iium.edu.my/42051/1/046_The_Generative_Capacity_of_Probabilistic_Splicing_Systems_%289-3_pp_1191-1198_2015%29.pdf
http://irep.iium.edu.my/42051/
http://dx.doi.org/10.12785/amis/090311
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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Summary:The concept of probabilistic splicing system was introduced as a model for stochastic processes using DNA computing techniques. In this paper we introduce splicing systems endowed with different continuous and discrete probabilistic distributions and call them as probabilistic splicing systems. We show that any continuous distribution does not increase the generative capacity of the probabilistic splicing systems with finite components, meanwhile, some discrete distributions increase their generative capacity up to context-sensitive languages. Finally, we associate certain thresholds with probabilistic splicing systems and this increases the computational power of splicing systems with finite components.