Modeling of RNA secondary structures using two-way quantum finite automata

Abstract Quantum finite automata (QFA) play a crucial role in quantum information processing theory. The representation of ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) structures using theory of automata had a great influence in the computer science. Investigation of the relationship between QFA and RNA structures is a natural goal. Two-way quantum finite automata (2QFA) is more dominant than its classical model in language recognition. Motivated by the concept of quantum finite automata, we have modeled RNA secondary structure loops such as, internal loop and double helix loop using two-way quantum finite automata. The major benefit of this approach is that these sequences can be parsed in linear time. In contrast, two-way deterministic finite automata (2DFA) cannot represent RNA secondary structure loops and two-way probabilistic finite automata (2PFA) can parse these sequences in exponential time. To the best of authors knowledge this is the first attempt to represent RNA secondary structure loops using two-way quantum finite automata.

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