alexa A Short Review of Deep Learning Neural Networks in Prot
ISSN: 2379-1764

Advanced Techniques in Biology & Medicine
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A Short Review of Deep Learning Neural Networks in Protein Structure Prediction Problems

Kuldip Paliwal*, James Lyons and Rhys Heffernan
Signal Processing Laboratory, School of Engineering, Griffith University, Brisbane, Australia
Corresponding Author : Kuldip Paliwal
Griffith School of Engineering, Griffith University,
Brisbane, QLD 4111, Australia
Tel: +61-7-3735 6536
Fax: +61-7-3735 5198
E-mail: [email protected]
Received: September 09, 2015; Accepted: September 17, 2015; Published: September 24, 2015
Citation: Paliwal K, Lyons J, Heffernan R (2015) A Short Review of Deep Learning Neural Networks in Protein Structure Prediction Problems. Adv Tech Biol Med 3:139. doi: 10.4172/2379-1764.1000139
Copyright: © 2015 Paliwal K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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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.


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