Management applications of expert systems
Information and Management
Parallel molecular computation
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures
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
Semantic Information Processing
Semantic Information Processing
Evolutionary neural networks and DNA computing algorithms for dual-axis motion control
Engineering Applications of Artificial Intelligence
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DNA computing has a lot of potential, in terms of ability to implement a relational database with circular molecules. In this work, a new DNA-based semantic model is proposed and described theoretically for implementing DNA based memories. This model, referred to as 'semantic model based on molecular computing' (SMC), has the structure of a graph formed by the set of all attribute-value pairs contained in the set of represented objects, plus a tag node for each object. Each path in the network, from an initial object-representing tag node to a terminal node represents the object named on the tag. Input of a set of input strands will result in the formation of object-representing dsDNAs via parallel self-assembly, from encoded ssDNAs representing (value, attribute)-pairs (nodes), as directed by ssDNA splinting strands representing relations (edges) in the network. The computational complexity of the implementation is estimated via simple simulation, which indicates the advantage of the approach over a sequential model. We believe that the semantic models are rather suitable for DNA-based memory, and that this proposal is the first such approach in the semantic networks area.