A NOVEL AND RELIABLE PROMOTER, PROTEIN CODING AND PROTEIN STRUCTURE PREDICTION USING ARTIFICIAL IMMUNE SYSTEM BASED 116-NEIGHBORHOOD HYBRID CELLULAR AUTOMATA

Abstract

The development of a potential classifier towards addressing Promoter, Protein Coding and Protein Structure Prediction was identified and the plan to achieve it was formulated. This research creates an intuition, how interrelated and logical problems in Bioinformatics like protein coding regions, promoter regions, protein structure prediction etc. can be addressed with a common framework.
The proposed approach aims at developing four independent classifiers which can perform their operations individually and also in a combined form. These classifiers AIS-MACA series uses the basic framework of Cellular Automata (CA) and features of the modified CLONAL classifier like self monitoring and non uniformity which is potential, versatile and robust. We use 16Neighborhood Hybrid Cellular Automata to design and develop our classifiers.