Communications of the ACM
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Experimental Construction of Very Large Scale DNA Databases with Associative Search Capability
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
Large-scale DNA memory based on the nested PCR
Natural Computing: an international journal
DNA memory with 16.8M addresses
DNA13'07 Proceedings of the 13th international conference on DNA computing
DNA computing: a research snapshot
Algorithms and theory of computation handbook
Graph-theoretic formalization of hybridization in DNA sticker complexes
DNA'11 Proceedings of the 17th international conference on DNA computing and molecular programming
A formal model for databases in DNA
ANB'10 Proceedings of the 4th international conference on Algebraic and Numeric Biology
Proceedings of the 16th International Conference on Database Theory
Graph-theoretic formalization of hybridization in DNA sticker complexes
Natural Computing: an international journal
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A DNA-based memory was implemented with in vitro learning and associative recall.The learning protocol stored the sequences to which it was exposed, and memories were recalled by sequence content through DNA-to-DNA template annealing reactions. Experiments demonstrated that biological DNA could be learned, that sequences similar to the training DNA were recalled correctly, and that unlike sequences were differentiated. Theoretically, the memory has a pattern separation capability that is very large, and can learn long DNA sequences. The learning and recall protocols are massively parallel, as well as simple, inexpensive, and quick. The memory has several potential applications in detection and classification of biological sequences, as well as a massive storage capacity for non-biological data.