@article { , title = {Predicting ?-turns and their types using predicted backbone dihedral angles and secondary structures}, abstract = {Background: β-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. Results: We have developed a novel method that predicts β-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of β-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of β-turn types I, II, IV, VIII and “non-specific”, achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. Conclusions: We have created an accurate predictor of b-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.}, eissn = {1471-2105}, journal = {BMC Bioinformatics}, publicationstatus = {Published}, publisher = {Springer Verlag}, url = {https://nottingham-repository.worktribe.com/output/1012802}, volume = {11}, year = {2010}, author = {Kountouris, Peter and Hirst, J.D.} }