BetaTPred statistics

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Citations per year

Number of citations per year for the bioinformatics software tool BetaTPred
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Tool usage distribution map

This map represents all the scientific publications referring to BetaTPred per scientific context
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Associated diseases

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Popular tool citations

chevron_left Secondary structure prediction Transmembrane beta-barrel prediction chevron_right
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BetaTPred specifications

Information


Unique identifier OMICS_06641
Name BetaTPred
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 2.0
Stability Stable
Maintained Yes

Versioning


No version available

Information


Unique identifier OMICS_06641
Name BetaTPred
Interface Web user interface
Restrictions to use None
Computer skills Basic
Version 2.0
Stability Stable
Maintained Yes

Publications for BetaTPred

BetaTPred citations

 (3)
library_books

Three Dimensional Structure Prediction of Fatty Acid Binding Site on Human Transmembrane Receptor CD36

2013
Bioinform Biol Insights
PMCID: 3859822
PMID: 24348024
DOI: 10.4137/BBI.S12276

[…] PSIPRED, BetaTPred2, and GAMMAPRED servers were used to predict the secondary structure of the target sequence, recognize helix, and strand and coil regions.Expasy ProtParam server determined the percentage of […]

library_books

Predicting beta turns in proteins using support vector machines with fractional polynomials

2013
Proteome Sci
PMCID: 3908855
PMID: 24565438
DOI: 10.1186/1477-5956-11-S1-S5

[…] UDES, which is based on propensities and multiple alignments. COUDES also utilizes secondary structure predicted by PSIPRED [], SSPRO2 [], and PROF []. The machine learning methods include BTPRED [], BetaTpred2 [], MOLEBRNN [] and NetTurnP [], which are based on artificial neural networks (ANNs), Kim's method based on k-nearest neighbor (KNN) [], as well as support vector machines (SVMs) based met […]

library_books

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

2008
BMC Bioinformatics
PMCID: 2613158
PMID: 18847492
DOI: 10.1186/1471-2105-9-430

[…] D [], SSPRO2 [], and PROF [] and the flanking residues around the β-turn tetrapeptide were also utilized by COUDES to improve the prediction accuracy.Machine learning based methods include BTPRED [], BetaTPred2 [,], and MOLEBRNN [] which are based on artificial neural networks (ANN), Kim's method [] which utilizes k-nearest neighbor (kNN), and four methods based on support vector machines (SVMs) [ […]


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BetaTPred institution(s)
Institute of Microbial Technology, Chandigarh, India

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