An efficient technique for protein classification using feature extraction by artificial neural networks

Classification, or supervised learning, is one of the major data mining processes. Protein classification focuses on predicting the function or the structure of new proteins. This can be done by classifying a new protein to a given family with previously known characteristics. There are many approaches available for classification tasks, such as statistical techniques, decision trees and the neural networks. In this paper, three types of neural networks such as feedforward neural network, probabilistic neural network and radial basis function neural network are implemented. The main objective of the paper is to build up an efficient classifier using neural networks. The measures used to estimate the performance of the classifier are Precision, Sensitivity and Specificity.