NEURAL NETWORK OPTIMIZATION FOR ESCHERICHIA-COLI PROMOTER PREDICTION

被引:115
作者
DEMELER, B
ZHOU, GW
机构
[1] Department of Biochemistry and Biophysics, Oregon State University, Corvallis
关键词
D O I
10.1093/nar/19.7.1593
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Methods for optimizing the prediction of Escherichia coli RNA polymerase promoter sequences by neural networks are presented. A neural network was trained on a set of 80 known promoter sequences combined with different numbers of random sequences. The conserved -10 region and -35 region of the promoter sequences and a combination of these regions were used in three independent training sets. The prediction accuracy of the resulting weight matrix was tested against a separate set of 30 known promoter sequences and 1500 random sequences. The effects of the network's topology, the extent of training, the number of random sequences in the training set and the effects of different data representations were examined and optimized. Accuracies of 100% on the promoter test set and 98.4% on the random test set were achieved with the optimal parameters.
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页码:1593 / 1599
页数:7
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