Abstract
A special class of n cell null boundary invertible three neighborhood CA referred to as Equal Length Cycle CA (ELCCA) is proposed in this paper to represent the features of n bit symbol strings. Necessary and sufficient conditions for generation of ELCCA has been reported. A specific set of ELCCA cycles are selected by employing the mRMR algorithm [2] popularly used for feature extraction of symbol strings. An algorithm is next developed to classify the symbol strings based on the feature set extracted. The proposed CA model has been validated for analyzing symbol string of biomolecules referred to as Enzymes. These biomolecules are classified on the basis of the catalytic reaction they participate. The symbol string classification algorithm predicts the class of any input enzyme with accuracy varying from 90.4% to 98.6%. Experimental results have been reported for 22800 enzymes with wide variation in species.
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Ghosh, S., Bachhar, T., Maiti, N.S., Mitra, I., Pal Chaudhuri, P. (2010). Theory and Application of Equal Length Cycle Cellular Automata (ELCCA) for Enzyme Classification. In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds) Cellular Automata. ACRI 2010. Lecture Notes in Computer Science, vol 6350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15979-4_5
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DOI: https://doi.org/10.1007/978-3-642-15979-4_5
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