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Bioinformatics incorporates information regarding biological data storage,accessing mechanisms and presentation of characteristics within this data. Mostof the problems in bioinformatics and be addressed efficiently by computertechniques. This paper aims at building a classifier based on MultipleAttractor Cellular Automata (MACA) which uses fuzzy logic with version Z topredict splicing site, protein coding and promoter region identification ineukaryotes. It is strengthened with an artificial immune system technique(AIS), Clonal algorithm for choosing rules of best fitness. The proposedclassifier can handle DNA sequences of lengths 54,108,162,252,354. Thisclassifier gives the exact boundaries of both protein and promoter regions withan average accuracy of 90.6%. This classifier can predict the splicing sitewith 97% accuracy. This classifier was tested with 1, 97,000 data componentswhich were taken from Fickett & Toung , EPDnew, and other sequences from arenowned medical university.

AIS-MACA- Z: MACA based Clonal Classifier for Splicing Site, Protein Coding and Promoter Region Identification in Eukaryotes