Title :
Prediction of protein secondary structure by multi-modal neural networks
Author :
Zhu, Hanxi ; Yoshihara, Lkuo ; Yamamori, Kunihito
Author_Institution :
Graduate Sch. of Eng., Miyazaki Univ., Japan
fDate :
6/24/1905 12:00:00 AM
Abstract :
We developed a multi-modal feed-forward neural network to predict the secondary structure of proteins. Several neural networks are used together and the final prediction results are decided by majority rule. We used 6137 residues to train and test the method. The average accuracy of the prediction is 66%, which is about 6.9% higher than single neural network
Keywords :
biology computing; feedforward neural nets; multilayer perceptrons; proteins; majority rule; multimodal feedforward neural network; neural network training; protein secondary structure; structure prediction; Amino acids; Cities and towns; Databases; Encoding; Feedforward neural networks; Feedforward systems; Multi-layer neural network; Neural networks; Protein engineering; Testing;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005483
