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Deep learning based techniques for pre training deep convolution neural networks
Deep learning based techniques for pre training deep convolution neural networks
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机译:基于深入训练深度卷积神经网络的基于深度学习技术
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摘要
The disclosed techniques include systems and methods for reducing the overfitting of neural network implementation models to handle an array of amino acids and associated positional specific frequency matrices.The system generates a benign and labelled supplemental training example sequence pair comprising an arrangement that moves the target amino acid position from the starting position to the end position.The complementary sequence pairs complement the virulence or benign missense training example sequence pairs.This has the same amino acid in the amino acid reference and alternative sequences.The system comprises logic for inputting the same supplemental training position specific frequency matrix (PFM) as a benign or pathogenic missense PFM at a matching start and end position along with each complementary array pair.The system comprises logic for weakening the effects of training PFM training during training the neural network implementation model by including supplementary training example PFM in training example data.
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