期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2010
卷号：2
期号：2
出版社：International Center for Scientific Research and Studies
摘要：Nucleic acid and protein sequences store a wealth of information which ultimately determines their functions and characteristics. Protein sequences classification deals with the assignment of sequences to known categories based on homology detection properties. In this paper, we developed a hybrid learning algorithm in neural network system called Neural Network Enzyme Classification (NNEC) to classify an enzyme found in Protein Data Bank (PDB) to a given family of enzymes. NNEC was developed based on Multilayer Perceptron with hybrid learning algorithm combining the genetic algorithm (GA) and Backpropagation (BP), where one of them acts as an operator in the other. Here, BP is used as a mutation-like-operator of the general GA search template. The proposed hybrid model was tested with different topologies of network architecture, especially in determining the number of hidden nodes. The precision results are quite promising in classifying the enzyme accordingly
关键词：enzyme; protein classification; neural networks; hybrid GA-BP
