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Bioinformatics encompass storing, analyzing and interpreting the biologicaldata. Most of the challenges for Machine Learning methods like CellularAutomata is to furnish the functional information with the correspondingbiological sequences. In eukaryotes DNA is divided into introns and exons. Theintrons will be removed to make the coding region by a process called splicing.By indentifying a splice site we can easily specify the DNA sequence category(Donor/Accepter/Neither).Splicing sites play an important role in understandingthe genes. A class of CA which can handle fuzzy logic is employed with modifiedclonal algorithm is proposed to identify the splicing site. This classifier istested with Irvine Primate Splice Junction Database. It is compared withNNspIICE, GENIO, HSPL and SPIICE VIEW. The reported accuracy and efficiency ofprediction is quite promising.

A Fast Multiple Attractor Cellular Automata with Modified Clonal Classifier for Splicing Site Prediction in Human Genome