Bacteria classification based on 16S ribosomal gene using artificial neural networks
CIMMACS'09 Proceedings of the 8th WSEAS International Conference on Computational intelligence, man-machine systems and cybernetics
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The fast growth of annotated biological data implies in the need of developing new techniques and tools to clas- sify these data, in such way that they can be useful. Pro- tein classification is one relevant task in this context. This paper presents different models of neural network, aiming to compare the influence of the protein sequence encoding method in the performance of the Neural network to clas- sify proteins. Besides, it is proposed two methods of protein sequence encoding, that were tested with several neural net- work, for classifying proteins using two approaches: based on families of proteins and based on function of proteins. The results of performance of the neural networks are pre- sented and compared with other works in the area.