Protein secondary structure: entropy, correlations and prediction.
about
The effect of long-range interactions on the secondary structure formation of proteinsHSEpred: predict half-sphere exposure from protein sequencesEvolution based on domain combinations: the case of glutaredoxinsAmino acid size, charge, hydropathy indices and matrices for protein structure analysis.CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks.Analysis and prediction of protein local structure based on structure alphabets.Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.Predicting secondary structures, contact numbers, and residue-wise contact orders of native protein structures from amino acid sequences using critical random networksSixty-five years of the long march in protein secondary structure prediction: the final stretch?Globally, unrelated protein sequences appear random.Analysis of an optimal hidden Markov model for secondary structure prediction.Predicting peptide structures in native proteins from physical simulations of fragmentsCargo Delivery into the Brain by in vivo identified Transport Peptides.A dynamic Bayesian network approach to protein secondary structure prediction.A sequence-compatible amount of native burial information is sufficient for determining the structure of small globular proteins.From local structure to a global framework: recognition of protein folds.Molecular dynamics simulation of the Escherichia coli NikR protein: equilibrium conformational fluctuations reveal interdomain allosteric communication pathways.Information-theoretic analysis and prediction of protein atomic burials: on the search for an informational intermediate between sequence and structure.Information and redundancy in the burial folding code of globular proteins within a wide range of shapes and sizes.Improved sequence-based prediction of strand residues.Clustering of protein structures using hydrophobic free energy and solvent accessibility of proteins.Prediction of One-Dimensional Structural Properties Of Proteins by Integrated Neural NetworksOn the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem
P2860
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P2860
Protein secondary structure: entropy, correlations and prediction.
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年学术文章
@wuu
2004年学术文章
@zh-cn
2004年学术文章
@zh-hans
2004年学术文章
@zh-my
2004年学术文章
@zh-sg
2004年學術文章
@yue
2004年學術文章
@zh
2004年學術文章
@zh-hant
name
Protein secondary structure: entropy, correlations and prediction.
@en
Protein secondary structure: entropy, correlations and prediction.
@nl
type
label
Protein secondary structure: entropy, correlations and prediction.
@en
Protein secondary structure: entropy, correlations and prediction.
@nl
prefLabel
Protein secondary structure: entropy, correlations and prediction.
@en
Protein secondary structure: entropy, correlations and prediction.
@nl
P356
P1433
P1476
Protein secondary structure: entropy, correlations and prediction.
@en
P2093
Gavin E Crooks
P304
P356
10.1093/BIOINFORMATICS/BTH132
P407
P577
2004-02-26T00:00:00Z
P5875
P698
P818
q-bio/0310034