Delineation of Techniques to implement on the enhanced proposed model   using data mining for protein sequence classification
  In post genomic era with the advent of new technologies a huge amount of complex molecular data are generated with high throughput. The management of this biological data is definitely a challenging task due to complexity and heterogeneity of data for discovering new knowledge. Issues like managing noisy and incomplete data are needed to be dealt with. Use of data mining in biological domain has made its inventory success. Discovering new knowledge from the biological data is a major challenge in data mining technique. The novelty of the proposed model is its combined use of intelligent techniques to classify the protein sequence faster and efficiently. Use of FFT, fuzzy classifier, String weighted algorithm, gram encoding method, neural network model and rough set classifier in a single model and in an appropriate place can enhance the quality of the classification system.Thus the primary challenge is to identify and classify the large protein sequences in a very fast and easy but intellectual way to decrease the time complexity and space complexity. 
Ananya Bose and Suprativ Saha
cs.DB cs.CE