Papers Protein Secondary Structure Prediction
“Protein Secondary Structure Prediction” 태그가 달린 논문 29편 · 필터 해제
Predicting protein secondary structure with Neural Machine Translation
We present analysis of a novel tool for protein secondary structure prediction using the recently-investigated Neural Machine Translation framework. The tool provides a fast and accurate folding prediction based on prima…
Machine TranslationPredictionProtein Secondary Structure PredictionTranslationReaching Optimized Parameter Set, Protein Secondary Structure Prediction Using Neural Network
We propose an optimized parameter set for protein secondary structure prediction using three layer feed forward back propagation neural network. The methodology uses four parameters viz. encoding scheme, window size, num…
Protein Secondary Structure PredictionSpecificityMUFold-SS: Protein Secondary Structure Prediction Using Deep Inception-Inside-Inception Networks
Motivation: Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning, which has been successfully applied to various research field…
image-classificationImage ClassificationPredictionProtein Secondary Structure PredictionNext-Step Conditioned Deep Convolutional Neural Networks Improve Protein Secondary Structure Prediction
Recently developed deep learning techniques have significantly improved the accuracy of various speech and image recognition systems. In this paper we show how to adapt some of these techniques to create a novel chained …
PredictionProtein Secondary Structure PredictionProtein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning
Recently developed deep learning techniques have significantly improved the accuracy of various speech and image recognition systems. In this paper we adapt some of these techniques for protein secondary structure predic…
Protein Secondary Structure PredictionProtein Structure PredictionProtein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks
Protein secondary structure prediction is an important problem in bioinformatics. Inspired by the recent successes of deep neural networks, in this paper, we propose an end-to-end deep network that predicts protein secon…
Multi-Task LearningProtein Secondary Structure PredictionProtein secondary structure prediction using deep convolutional neural fields
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% Q…
PredictionProtein Secondary Structure PredictionProtein Secondary Structure Prediction with Long Short Term Memory Networks
Prediction of protein secondary structure from the amino acid sequence is a classical bioinformatics problem. Common methods use feed forward neural networks or SVMs combined with a sliding window, as these models does n…
Protein Secondary Structure PredictionDeep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
Predicting protein secondary structure is a fundamental problem in protein structure prediction. Here we present a new supervised generative stochastic network (GSN) based method to predict local secondary structure with…
PredictionProtein Secondary Structure PredictionProtein Structure Prediction