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Mini Review Open Access
Determining the structure of a protein given its sequence is a challenging problem. Deep learning is a rapidly evolving field which excels at problems where there are complex relationships between input features and desired outputs. Deep Neural Networks have become popular for solving problems in protein science. Various deep neural network architectures have been proposed including deep feed-forward neural networks, recurrent neural networks and more recently neural Turing machines and memory networks. This article provides a short review of deep learning applied to protein prediction problems.
Deep neural networks, Recurrent neural networks, Protein structure prediction, Molecular Biology Techniques, Radiolabelling Techniques in Biology, Structural Biology Techniques