(Q30377761)

21 June 2017

title

Prediction of beta-turn in protein using E-SSpred and support vector machine. (English)

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21 June 2017

main subject

support vector machine

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2

Yaping Fang

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21 June 2017

Lirong Liu

1

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21 June 2017

Menglong Li

series ordinal

3

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21 June 2017

Cuicui Wang

series ordinal

4

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21 June 2017

publication date

1 May 2009

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21 June 2017

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21 June 2017

volume

28

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21 June 2017

issue

3-4

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21 June 2017

page(s)

175-181

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Predicting protein secondary structure and solvent accessibility with an improved multiple linear regression method.

21 June 2017

cites work

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12 December 2020

Helix signals in proteins

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12 December 2020

Detecting hidden sequence propensity for amyloid fibril formation

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12 December 2020

Protein beta-turn prediction using nearest-neighbor method.

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12 December 2020

Protein secondary structure prediction based on position-specific scoring matrices

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12 December 2020

Prediction of the location and type of beta-turns in proteins using neural networks.

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12 December 2020

The limits of protein secondary structure prediction accuracy from multiple sequence alignment.

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12 December 2020

Prediction of protein secondary structure at better than 70% accuracy

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12 December 2020

The anatomy and taxonomy of protein structure

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12 December 2020

Prediction of mitochondrial proteins based on genetic algorithm - partial least squares and support vector machine

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Amino acid preferences for specific locations at the ends of alpha helices

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12 December 2020

Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features

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12 December 2020

A revised set of potentials for beta-turn formation in proteins

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12 December 2020

Beta-turns and their distortions: a proposed new nomenclature

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12 December 2020

Predicting DNA-binding proteins: approached from Chou's pseudo amino acid composition and other specific sequence features

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PROMOTIF--a program to identify and analyze structural motifs in proteins

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A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach.

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12 December 2020

Evaluation and improvement of multiple sequence methods for protein secondary structure prediction.

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12 December 2020

Improved method for predicting beta-turn using support vector machine

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12 December 2020

Prediction of beta-turns in proteins using neural networks.

1 reference

12 December 2020

Prediction and analysis of beta-turns in proteins by support vector machine

1 reference

12 December 2020

Turns in peptides and proteins

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12 December 2020

Protein secondary structure prediction based on an improved support vector machines approach

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12 December 2020

Rules for alpha-helix termination by glycine

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12 December 2020

An evaluation of beta-turn prediction methods.

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12 December 2020

Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences

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12 December 2020

Prediction of beta-turns in proteins from multiple alignment using neural network

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12 December 2020

Prediction of tight turns and their types in proteins.

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12 December 2020

Using support vector machine to predict beta- and gamma-turns in proteins

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12 December 2020

Position-specific residue preference features around the ends of helices and strands and a novel strategy for the prediction of secondary structures.

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12 December 2020

Redefining the goals of protein secondary structure prediction

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12 December 2020

Role of amino acid residues at turns in the conformational stability and folding of human lysozyme

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12 December 2020

Relative helix-forming tendencies of nonpolar amino acids

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12 December 2020

High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

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Structural basis of amino acid alpha helix propensity

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12 December 2020

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

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12 December 2020

A novel method for protein secondary structure prediction using dual-layer SVM and profiles.

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12 December 2020

Prediction of beta-turns and beta-turn types by a novel bidirectional Elman-type recurrent neural network with multiple output layers (MOLEBRNN).

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12 December 2020

Predicting G-protein coupled receptors-G-protein coupling specificity based on autocross-covariance transform.

1 reference

12 December 2020

A neural network method for prediction of beta-turn types in proteins using evolutionary information.

1 reference

12 December 2020

Conformational parameters for amino acids in helical, beta-sheet, and random coil regions calculated from proteins

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12 December 2020

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

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12 December 2020

Support vector machines for the classification and prediction of ?-turn types

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12 December 2020

Chain reversals in proteins

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12 December 2020

Combining evolutionary information and neural networks to predict protein secondary structure

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12 December 2020

10.1007/S10930-009-9181-4

Identifiers

DOI

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21 June 2017

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