The aim of BetaTPred2 server is to predict Beta turns in proteins from multiple alignment by using neural network from the given amino acid sequence. For ? turn prediction, it uses the position specific score matrices generated by PSI-BLAST and secondary structure predicted by PSIPRED. The net is trained and tested on a set of 426 non-homologous protein chains with 7-fold cross-validation. It predicts ? turns in proteins with residue accuracy of 75.5% and MCC value of 0.43.
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Kaur, H. and Raghava, G.P.S.
Prediction of beta-turns in proteins from multiple alignment using neural network.
Protein Science 2003 12: 627-634