A Review on Predict the Frequent Pattern of Amino Acids using Data mining Techniques

In recent years, rapid developments in genomics and proteomics have generated a large amount of biological data. So A critical problem in biological data analysis is to classify the biological sequences and structures based on their critical features and functions. Protein is one among the important factor and acts as the constituents of all living organisms. Protein plays the most predominant role for causing viral diseases like viral fever, fluid diseases, poliomyelitis, hepatitis, swine flu, tumour, etc. Our approach aims at extracting the hidden and the most dominating amino acids among the infected protein sequence which causes some infections in human. We handle this problem by predicting patterns apply strong association rules along with genetic algorithm and fuzzy logic provides a way to obtain interesting correlations and patterns from datasets. It also eliminates human error and provides high accuracy of results.