Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Introduction to Algorithms
Strand design for biomolecular computation
Theoretical Computer Science - Natural computing
DNA sequence design using templates
New Generation Computing
Biomolecular Computation in Virtual Test Tubes
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
A Software Tool for Generating Non-crosshybridizing Libraries of DNA Oligonucleotides
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
Software Tools for DNA Sequence Design
Genetic Programming and Evolvable Machines
Self-Assembly of DNA-like Structures In Silico
Genetic Programming and Evolvable Machines
Codeword design and information encoding in DNA ensembles
Natural Computing: an international journal
Sensitivity and capacity of microarray encodings
DNA'05 Proceedings of the 11th international conference on DNA Computing
In search of optimal codes for DNA computing
DNA'06 Proceedings of the 12th international conference on DNA Computing
Characterization of non-crosshybridizing DNA oligonucleotides manufactured In Vitro
DNA'04 Proceedings of the 10th international conference on DNA computing
A weighted insertion-deletion stacked pair thermodynamic metric for DNA codes
DNA'04 Proceedings of the 10th international conference on DNA computing
The capacity of DNA for information encoding
DNA'04 Proceedings of the 10th international conference on DNA computing
Randomized fast design of short DNA words
ACM Transactions on Algorithms (TALG)
Theory and applications of DNA codeword design
TPNC'12 Proceedings of the First international conference on Theory and Practice of Natural Computing
Generating DNA code words using forbidding and enforcing systems
TPNC'12 Proceedings of the First international conference on Theory and Practice of Natural Computing
Deterministic polynomial-time algorithms for designing short DNA words
Theoretical Computer Science
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Finding a large set of single DNA strands that do not crosshybridize to themselves and/or to their complements is an important problem in DNA computing, self-assembly, and DNA memories. We describe a theoretical framework to analyze this problem, gauge its computational difficulty, and provide nearly optimal solutions. In this framework, codeword design is reduced to finding large sets of strands maximaly separated in a DNA space and the size of such sets depends on the geometry of these metric spaces. We show that codeword design is NP-complete using any single reasonable measure that approximates the Gibbs energy, thus practically excluding the possibility of finding any procedure to find maximal sets efficiently. Second, we extend a technique known as shuffling to provide a construction that yields provably nearly-maximal codes. Third, we propose a filtering process that removes strands creating pairs with low Gibbs energies, as approximated by the nearest-neighbor model. These two steps produce large codes of thermodynamic high quality. The proposed framework can be used to gain an understanding of the Gibbs energy landscapes for DNA strands on which much of DNA computing and self-assembly are based.