about
Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure predictionToward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks.Accurate single-sequence prediction of solvent accessible surface area using local and global featuresSP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty modelImproving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.Effective protein conformational sampling based on predicted torsion angles.Density Estimation for Protein Conformation Angles Using a Bivariate von Mises Distribution and Bayesian Nonparametrics.iFC²: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content.Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction.Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X.Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile.Sixty-five years of the long march in protein secondary structure prediction: the final stretch?Trends in template/fragment-free protein structure predictionCapturing Non-Local Interactions by Long Short Term Memory Bidirectional Recurrent Neural Networks for Improving Prediction of Protein Secondary Structure, Backbone Angles, Contact Numbers, and Solvent Accessibility.Prediction of backbone dihedral angles and protein secondary structure using support vector machines.TANGLE: two-level support vector regression approach for protein backbone torsion angle prediction from primary sequencesEvaluation of protein dihedral angle prediction methods.SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion anglesIntegrated Strategy Improves the Prediction Accuracy of miRNA in Large Dataset.Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network.From local structure to a global framework: recognition of protein folds.Deep learning methods for protein torsion angle prediction.Predicting residue-residue contact maps by a two-layer, integrated neural-network methodBackbone Dihedral Angle Prediction.Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction.sDFIRE: Sequence-specific statistical energy function for protein structure prediction by decoy selections.A genetic algorithm encoded with the structural information of amino acids and dipeptides for efficient conformational searches of oligopeptides.RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.Prediction of One-Dimensional Structural Properties Of Proteins by Integrated Neural Networks
P2860
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P2860
description
2008 nî lūn-bûn
@nan
2008 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Real-value prediction of backbone torsion angles.
@ast
Real-value prediction of backbone torsion angles.
@en
type
label
Real-value prediction of backbone torsion angles.
@ast
Real-value prediction of backbone torsion angles.
@en
prefLabel
Real-value prediction of backbone torsion angles.
@ast
Real-value prediction of backbone torsion angles.
@en
P2093
P2860
P356
P1433
P1476
Real-value prediction of backbone torsion angles.
@en
P2093
P2860
P304
P356
10.1002/PROT.21940
P407
P577
2008-07-01T00:00:00Z