The architecture of our β -turn location and β -turn type prediction method. An example of an input sequence is provided at the top. Around each residue to be predicted (shown in red), two local windows are used. One, l1, has a size of nine residues and is used for the PSSM values, while the other, l2, takes in account the predicted secondary structures and dihedral angles for five residues. After running PSI-BLAST , the PSSM values are linearly scaled and transformed into a vector of 180 attributes (i.e. a local window of nine residues, l1). DISSPred  utilises PSSMs to predict three-state secondary structures and seven-state dihedral angles, which are transformed into a vector of 50 attributes using a window of five residues (l2). The two vectors are merged to create the final input vector for the SVM classifiers. Lastly, the predictions are filtered to give the final result.