SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model
about
Prodepth: predict residue depth by support vector regression approach from protein sequences onlyLow-homology protein threadingImproving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templatesRaptorX: exploiting structure information for protein alignment by statistical inferencePredicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure predictionA conditional neural fields model for protein threadingHierarchical classification of protein folds using a novel ensemble classifierImprovement in low-homology template-based modeling by employing a model evaluation method with focus on topology.Enhancing HMM-based protein profile-profile alignment with structural features and evolutionary coupling informationDetecting local residue environment similarity for recognizing near-native structure models.Improving protein fold recognition by random forest.A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation.BCL::contact-low confidence fold recognition hits boost protein contact prediction and de novo structure determination.Template-based protein modeling: recent methodological advances.DescFold: a web server for protein fold recognition.Effect of using suboptimal alignments in template-based protein structure prediction.Incorporation of local structural preference potential improves fold recognition.QSE: A new 3-D solvent exposure measure for the analysis of protein structure.CONTSOR--a new knowledge-based fold recognition potential, based on side chain orientation and contacts between residue terminal groups.Template-based protein structure modeling using the RaptorX web server.TANGLE: two-level support vector regression approach for protein backbone torsion angle prediction from primary sequencesEvaluation of protein dihedral angle prediction methods.Refinement by shifting secondary structure elements improves sequence alignments.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.ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble ClassifierFrom local structure to a global framework: recognition of protein folds.Improving Protein Fold Recognition by Deep Learning Networks.Template-based structure prediction and classification of transcription factors in Arabidopsis thalianaBackbone Dihedral Angle Prediction.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 NetworksA Topology Structure Based Outer Membrane Proteins Segment Alignment Method
P2860
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P2860
SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model
description
2008 nî lūn-bûn
@nan
2008 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հունիսին 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
SP5: improving protein fold re ...... rofile-based gap penalty model
@ast
SP5: improving protein fold re ...... rofile-based gap penalty model
@en
type
label
SP5: improving protein fold re ...... rofile-based gap penalty model
@ast
SP5: improving protein fold re ...... rofile-based gap penalty model
@en
prefLabel
SP5: improving protein fold re ...... rofile-based gap penalty model
@ast
SP5: improving protein fold re ...... rofile-based gap penalty model
@en
P2860
P1433
P1476
SP5: improving protein fold re ...... rofile-based gap penalty model
@en
P2093
P2860
P356
10.1371/JOURNAL.PONE.0002325
P407
P50
P577
2008-06-04T00:00:00Z