Original paper
Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields
Abstract
Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is...
Paper Details
Title
Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields
Published Date
Jan 11, 2016
Journal
Volume
6
Issue
1
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