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JSSPrediction: a Framework to Predict Protein Secondary Structures Using Integration

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5 Author(s)

Identifying protein secondary structures is a difficult task. Recently, a lot of software tools for protein secondary structure 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 (U) integrate the prediction results of the selected prediction tools. Experimental results are also reported

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Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on

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