Predicting the secondary structure of a protein is a main topic in bioinformatics. A reliable predictor is needed by threading methods to improve the prediction of tertiary structure. Moreover, the predicted secondary structure content of a protein can be used to assign the protein to a specific folding class and thus estimate its function. We discuss here the use of support vector machines (SV...

In Bioinformatics, Protein Secondary Structure Prediction (PSSP) has been considered as one of the main challenging tasks in this field. Today, secondary structure protein prediction approaches have been categorized into three groups (Neighbor-based, model-based, and meta predicator-based model). The main purpose of the model-based approaches is to detect the protein sequence-structure by utili...

Most current methods for prediction of protein secondary structure use a small window of the protein sequence to predict the structure of the central amino acid. We describe a new method for prediction of the non-local structure called ,8-sheet, which consists of two or more ,8-strands that are connected by hydrogen bonds. Since,8strands are often widely separated in the protein chain , a netwo...