Protein Classification Using N-gram Technique and Association Rules

The knowledge extraction process from biological data is increasingly being considered, it addresses general issues such as grouping, classification and association; The Protein classification is an important activity for the biologist to respond to biological needs. For this reason, the authors present a global framework inspired by the knowledge extraction process from biological data to classified proteins from their primary structure based on the association rules. This framework has three main steps: The first one is, the pre-processing phase, consists of extracting descriptors by N-Gram technique. The second is the extraction of associations rules, applying the Apriori algorithm. The third step is selecting the relevant rules, and applied the classifier. The experiments of this technique were performed on five classes of protein, extracted from UniProt data bank and compared with five classification methods in the WEKA platform. The obtained results satisfied the authors' purpose to propose an effective protein classifier supported by the N-gram technique and the Apriori algorithm.