A hybrid genetic-neural system for predicting protein secondary structure

ARMANO, GIULIANO;MANCOSU G;MILANESI L;ORRO, ALESSANDRO;SABA, MASSIMILIANO;VARGIU, ELOISA

2005-01-01

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Abstract

Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experimental data on protein structures available in public databases, the gap between known sequences and known tertiary structures is constantly increasing. The need for automatic methods has brought the development of several prediction and modelling tools, but a general methodology able to solve the problem has not yet been devised, and most methodologies concentrate on the simplified task of predicting secondary structure.