Host: Japan Society for Fuzzy Theory and Intelligent Informatics
Co-host: International Fuzzy Systems Association, IEEE Computational Intelligence Society Japan Chapter
In this paper, we propose a novel approach to inference system with a DNA-based semantic knowledge representation model. DNA Computing-inspired Semantic Network (DCSN) is theoretically proposed and constructed with DNA molecules. It has the network structure of a graph formed by the set of all attribute-attribute values pairs contained in the set of represented objects, plus two tag nodes for each object. Each path in the network, from an initial tag node to a terminal tag node, represents the object named on the tag. To verify our theory, the preliminary experiment on implementing of inference system with a small model was successfully done by using very simple techniques, Parallel Overlap Assembly (POA) method, Polymerase Chain Reaction (PCR), and gel electrophoresis. The proposed model is very suitable for DNA-based knowledge representation in order to store vast amount of information with high density.
