TY - GEN

T1 - Probabilistic simple splicing systems

AU - Selvarajoo, Mathuri

AU - Heng, Fong Wan

AU - Sarmin, Nor Haniza

AU - Turaev, Sherzod

PY - 2014

Y1 - 2014

N2 - A splicing system, one of the early theoretical models for DNA computing was introduced by Head in 1987. Splicing systems are based on the splicing operation which, informally, cuts two strings of DNA molecules at the specific recognition sites and attaches the prefix of the first string to the suffix of the second string, and the prefix of the second string to the suffix of the first string, thus yielding the new strings. For a specific type of splicing systems, namely the simple splicing systems, the recognition sites are the same for both strings of DNA molecules. It is known that splicing systems with finite sets of axioms and splicing rules only generate regular languages. Hence, different types of restrictions have been considered for splicing systems in order to increase their computational power. Recently, probabilistic splicing systems have been introduced where the probabilities are initially associated with the axioms, and the probabilities of the generated strings are computed from the probabilities of the initial strings. In this paper, some properties of probabilistic simple splicing systems are investigated. We prove that probabilistic simple splicing systems can also increase the computational power of the splicing languages generated.

AB - A splicing system, one of the early theoretical models for DNA computing was introduced by Head in 1987. Splicing systems are based on the splicing operation which, informally, cuts two strings of DNA molecules at the specific recognition sites and attaches the prefix of the first string to the suffix of the second string, and the prefix of the second string to the suffix of the first string, thus yielding the new strings. For a specific type of splicing systems, namely the simple splicing systems, the recognition sites are the same for both strings of DNA molecules. It is known that splicing systems with finite sets of axioms and splicing rules only generate regular languages. Hence, different types of restrictions have been considered for splicing systems in order to increase their computational power. Recently, probabilistic splicing systems have been introduced where the probabilities are initially associated with the axioms, and the probabilities of the generated strings are computed from the probabilities of the initial strings. In this paper, some properties of probabilistic simple splicing systems are investigated. We prove that probabilistic simple splicing systems can also increase the computational power of the splicing languages generated.

KW - Computational Power

KW - DNA Computing

KW - Probability

KW - Regular Languages

KW - Simple Splicing Systems

UR - http://www.scopus.com/inward/record.url?scp=84904107165&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904107165&partnerID=8YFLogxK

U2 - 10.1063/1.4882571

DO - 10.1063/1.4882571

M3 - Conference contribution

AN - SCOPUS:84904107165

SN - 9780735412361

T3 - AIP Conference Proceedings

SP - 760

EP - 766

BT - Proceedings of the 3rd International Conference on Mathematical Sciences, ICMS 2013

PB - American Institute of Physics Inc.

T2 - 3rd International Conference on Mathematical Sciences, ICMS 2013

Y2 - 17 December 2013 through 19 December 2013

ER -