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During the past decade, with the significant progress of computational power as well as ever-rising data availability, deep learning techniques became increasingly popular due to their excellent performance on computer vision problems.
A Simple Method for Displaying the Hydropathic Character of a Protein
Jack Kyte and Russel F. Doolittle · 1982
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Organic Chemistry
Leroy G. Wade · 2002
Earlier work this paper cites.
Predicting Enzyme Class From Protein Structure Without Alignments
Paul D. Dobson and Andrew J. Doig · 2005
Earlier work this paper cites.
Biopython: freely available Python tools for computational molecular biology and bioinformatics
Peter J.A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski, and Michiel J.L. de Hoon · 2009
Earlier work this paper cites.
A systematic analysis of performance measures for classification tasks
Marina Sokolova and Guy Lapalme · 2009
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A top-down approach to classify enzyme functional classes and sub-classes using random forest
Chetan Kumar and Alok Choudhary · 2012
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
32nd International Conference on Machine Learning · 2015
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TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems
Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Lei Ba · 2015
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VoxNet: A 3D Convolutional Neural Network for Real-Time Object Recognition
Daniel Maturana and Sebastian Scherer · 2015
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HCP: A Flexible CNN Framework for Multi-Label Image Classification
Yunchao Wei, Wei Xia, Junshi Huang, Bingbing Ni, Jian Dong, Yao Zhao, and Shuicheng Yan · 2015
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Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock, Theodore Lim, J.M. Ritchie, and Nick Weston · 2016
Cited alongside, same era.
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction
Zeming Lin, Jack Lanchantin, and Yanjun Qi · 2016
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Systematic evaluation of cnn advances on the imagenet
Dmytro Mishkin, Nikolay Sergievskiy, and Jiri Matas · 2016
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3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients
Dong Nie, Han Zhang, Ehsan Adeli, Luyan Liu, and Dinggang Shen · 2016
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Automatic single- and multi-label enzymatic function prediction by machine learning
Shervine Amidi, Afshine Amidi, Dimitrios Vlachakis, Nikos Paragios, and Evangelia I Zacharaki · 2017
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Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
Konstantinos Kamnitsas, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, and Ben Glocker · 2017
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Mental Disease Feature Extraction with MRI by 3D Convolutional Neural Network with Multi-channel Input
Lijun Cao, Zhi Liu, Xiaofu He, Yankun Cao, and Ke-ning Li · 2016
Cited alongside, same era.
FusionNet: 3D Object Classification Using Multiple Data Representations
Vishakh Hegde and Reza Zadeh · 2016
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Prediction of protein function using a deep convolutional neural network ensemble
Evangelia I Zacharaki · 2017
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Application of Multi-channel 3D-cube Successive Convolution Network for Convective Storm Nowcasting
Wei Zhang, Lei Han, Juanzhen Sun, Hanyang Guo, and Jie Dai · 2017
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