Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
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)
A Clause String DNA Algorithm for SAT
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
Shortening the Computational Time of the Fluorescent DNA Computing
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
DNA and Membrane Algorithms for SAT
Fundamenta Informaticae - Membrane Computing (WMC-CdeA2001)
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We propose a strategy using tiny beads for DNA computing. DNA computing is a means of solving intractable computation problems such as NP-complete problems. In our strategy, each bead carries multiple copies of a DNA sequence, and each sequence represents a candidate solution for a given problem. Calculation in our strategy is executed by competitive hybridization of two types of fluorescent sequences on the beads. One type of fluorescent sequences represents a constraint that has not been satisfied, and the other type a constraint that has been satisfied. After competitive hybridization, beads with only the latter type of fluorescent sequences hold "true" solutions. To extract the beads from the test tube, we use fluorescent-activated cell sorter.We describe the approach to DNA computing on beads through SAT problems. The SAT problem is an NP-complete problem in Boolean logic. Using Megaclone, which allows DNA strands to be attached to beads, we show that DNA computing on beads can solve up to 24 variables.