On the computational power of DNA
Discrete Applied Mathematics - Special volume on computational molecular biology
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
A machine program for theorem-proving
Communications of the ACM
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
An Improved Exponential-Time Algorithm for k-SAT
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Breadth First Search 3SAT Algorithms for DNA Computers
Breadth First Search 3SAT Algorithms for DNA Computers
Circuits, cnfs, and satisfiability
Circuits, cnfs, and satisfiability
Solving satisfiability in less than 2n steps
Discrete Applied Mathematics
Solving Constraint Satisfaction Problems with DNA Computing
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Implementation of a Random Walk Method for Solving 3-SAT on Circular DNA Molecules
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
How Efficiently Can Room at the Bottom Be Traded Away for Speed at the Top?
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
A DNA-Based genetic algorithm implementation for graph coloring problem
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Efficient 3-SAT algorithms in the tile assembly model
Natural Computing: an international journal
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We present a randomized DNA algorithm for k-SAT based on the classical algorithm of Paturi et al. [8]. For an n-variable, m-clause instance of k-SAT (m n), our algorithm finds a satisfying assignment, assuming one exists, with probability 1-e-α, in worst-case time O(k2mn) and space O(2(1-1/k)n+log α). This makes it the most space-efficient DNA k-SAT algorithm for k 3 and k n=log α (i.e. the clause size is small compared to the number of variables). In addition, our algorithm is the first DNA algorithm to adapt techniques from the field of randomized classical algorithms.