Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique

Abstract

The proposed Neural-Fuzzy pattern recognition (NFPR) system discussed in this paper effectively reduces the complication in precisely analyzing and interpreting human deoxyribonucleic acid (DNA) sample. In this novel approach, the perfect blend made of bioinformatics and a competitive method of neural networks technique, which has the advantage over conventional computation technique, in their ability to solve problem that do not have an algorithmic solution or the available solutions are also too complex to be found, results in efficient DNA pattern analysis algorithm that identifies repeated patterns in the given human DNA sample assisting in generation of unique identification number of an individual, location of occurrence of mutation in the mutated DNA sample with utmost prediction accuracy. Key words: Neural-Fuzzy resonance mapping, competitive learning, NFPR processor, Input generator, preprocessor, discriminator, DNA profiling, DNA sequence, FASTA format.