One contact for every twelve residues allows robust and accurate topology-level protein structure modeling
about
Protein folding and de novo protein design for biotechnological applicationsAutomated procedure for contact-map-based protein structure reconstruction.Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning ModelAccurate contact predictions using covariation techniques and machine learning.Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.Large-scale determination of previously unsolved protein structures using evolutionary informationAnalysis of free modeling predictions by RBO aleph in CASP11.Contact-assisted protein structure modeling by global optimization in CASP11.Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11.Assessment of CASP11 contact-assisted predictions.Recent advances in sequence-based protein structure prediction.ConEVA: a toolbox for comprehensive assessment of protein contacts.Protein structure determination using metagenome sequence data.Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.Deep mutational scanning: a new style of protein scienceCoinFold: a web server for protein contact prediction and contact-assisted protein foldingComparing co-evolution methods and their application to template-free protein structure prediction.KScons: a Bayesian approach for protein residue contact prediction using the knob-socket model of protein tertiary structure.R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.Improving Protein Fold Recognition by Extracting Fold-specific Features from Predicted Residue-residue Contacts.Assessment of contact predictions in CASP12: co-evolution and deep learning coming of age.Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks.Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction.Exploring the effects of sparse restraints on protein structure prediction.Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.Finding the needle in the haystack: towards solving the protein-folding problem computationally.bbcontacts: prediction of β-strand pairing from direct coupling patterns.Analysis of deep learning methods for blind protein contact prediction in CASP12.Identification of residue pairing in interacting β-strands from a predicted residue contact map.Contact prediction is hardest for the most informative contacts, but improves with the incorporation of contact potentials.
P2860
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P2860
One contact for every twelve residues allows robust and accurate topology-level protein structure modeling
description
2013 nî lūn-bûn
@nan
2013 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
One contact for every twelve r ...... vel protein structure modeling
@ast
One contact for every twelve r ...... vel protein structure modeling
@en
type
label
One contact for every twelve r ...... vel protein structure modeling
@ast
One contact for every twelve r ...... vel protein structure modeling
@en
prefLabel
One contact for every twelve r ...... vel protein structure modeling
@ast
One contact for every twelve r ...... vel protein structure modeling
@en
P2093
P2860
P356
P1433
P1476
One contact for every twelve r ...... vel protein structure modeling
@en
P2093
David E Kim
Frank Dimaio
Ray Yu-Ruei Wang
Yifan Song
P2860
P304
P356
10.1002/PROT.24374
P407
P478
82 Suppl 2
P50
P577
2013-09-10T00:00:00Z