DocumentCode
1645509
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
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
280
Lastpage
285
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005483
Filename
1005483
Link To Document