ANGLOR: A Composite Machine-Learning Algorithm for Protein Backbone Torsion Angle Prediction

Sitao Wu and Yang Zhang

PLOS ONE, 2008, vol. 3, issue 10, 1-8

Abstract: We developed a composite machine-learning based algorithm, called ANGLOR, to predict real-value protein backbone torsion angles from amino acid sequences. The input features of ANGLOR include sequence profiles, predicted secondary structure and solvent accessibility. In a large-scale benchmarking test, the mean absolute error (MAE) of the phi/psi prediction is 28°/46°, which is ∼10% lower than that generated by software in literature. The prediction is statistically different from a random predictor (or a purely secondary-structure-based predictor) with p-value

Date: 2008
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0003400

DOI: 10.1371/journal.pone.0003400

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