JSSPrediction: a Framework to Predict Protein Secondary Structures Using Integration

Identifying protein secondary structures is a difficult task. Recently, a lot of software tools for protein secondary structures prediction have been produced and made available on-line, mostly with good performances. However, prediction tools work correctly for families of proteins, such that users have to know which predictor to use for a given unknown protein. We propose a framework to improve secondary structure prediction by integrating results obtained from a set of available predictors. Our contribution consists in the definition of a two phase approach: (i) select a set of predictors which have good performances with the unknown protein family, and (ii) integrate the prediction results of the selected prediction tools. Experimental results are also reported.

• Type: Conference
• Year: 2006
• Where: CBMS
• Authors: Luigi Palopoli, Simona E. Rombo, Giorgio Terracina, Giuseppe Tradigo, Pierangelo Veltri
• Keywords: CBMS 2006, Medical Imaging, Prediction, Prediction Tools, Protein Secondary Structures