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CA has grown as potential classifier for addressing major problems inbioinformatics. Lot of bioinformatics problems like predicting the proteincoding region, finding the promoter region, predicting the structure of proteinand many other problems in bioinformatics can be addressed through CellularAutomata. Even though there are some prediction techniques addressing theseproblems, the approximate accuracy level is very less. An automated procedurewas proposed with MACA (Multiple Attractor Cellular Automata) which can addressall these problems. The genetic algorithm is also used to find rules with goodfitness values. Extensive experiments are conducted for reporting the accuracyof the proposed tool. The average accuracy of MACA when tested with ENCODE,BG570, HMR195, Fickett and Tongue, ASP67 datasets is 78%.

Multiple Attractor Cellular Automata (MACA) for Addressing Major Problems in Bioinformatics