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19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06) (2006)
Salt Lake City, Utah
June 22, 2006 to June 23, 2006
ISSN: 1063-7125
ISBN: 0-7695-2517-1
pp: 931-935
L. Palopoli , Universita della Calabria, Italy
S. E. Rombo , Universita "Mediterranea" di Reggio Calabria, Italy
G. Terracina , Universita della Calabria, Italy
G. Tradigo , ICAR-CNR, Italy
P. Veltri , Universita "Magna Gr?cia" di Catanzaro, Italy
ABSTRACT
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 (ii) integrate the prediction results of the selected prediction tools. Experimental results are also reported.
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CITATION

P. Veltri, G. Tradigo, S. E. Rombo, L. Palopoli and G. Terracina, "JSSPrediction: a Framework to Predict Protein Secondary Structures Using Integration," 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)(CBMS), Salt Lake City, Utah, 2006, pp. 931-935.
doi:10.1109/CBMS.2006.103
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