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