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 -