Handbook of Formal Languages
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Solving the Round Robin Problem Using Propositional Logic
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A Proposal of DNA Computing on Beads with Application to SAT Problems
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
DNASequencesGenerator: A Program for the Construction of DNA Sequences
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
DNA Computing: New Computing Paradigms (Texts in Theoretical Computer Science. An EATCS Series)
DNA Computing: New Computing Paradigms (Texts in Theoretical Computer Science. An EATCS Series)
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Hi-index | 0.00 |
We present a method to shorten the computational time of the fluorescent DNA computing. Fluorescent DNA computing is proposed to solve intractable computation problems such as SAT problems. They use two groups of fluorescent DNA strands. One group of fluorescent DNA represents that a constraint of the given problem is satisfied, and another group represents that a constraint is unsatisfied. The calculation is executed by hybridizing them competitively to DNA beads or spots on DNA microarray. Though the biological operation used in the fluorescent DNA computing is simple, it needs the same number of beads or spots on microarray as the number of candidate solutions. In this paper, we prove that one bead or spot can represent plural candidate solutions through SAT problem, and show the algorithm and an experimental result of the fluorescent DNA computing.