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MASSP3: A System for Predicting Protein Secondary Structure

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Author(s): Armano Giuliano | Orro Alessandro | Vargiu Eloisa

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2006;
Issue: 1;
Start page: 017195;
Date: 2006;
Original page

ABSTRACT
A system that resorts to multiple experts for dealing with the problem of predicting secondary structures is described, whose performances are comparable to those obtained by other state-of-the-art predictors. The system performs an overall processing based on two main steps: first, a "sequence-to-structure" prediction is performed, by resorting to a population of hybrid genetic-neural experts, and then a "structure-to-structure" prediction is performed, by resorting to a feedforward artificial neural networks. To investigate the performance of the proposed approach, the system has been tested on the RS126 set of proteins. Experimental results (about 76% of accuracy) point to the validity of the approach.
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