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Here we propose an approach to include global structural information in the secondary structure prediction procedure based on hidden Markov models (HMMs) of protein folds. We first identify the correct fold or 'topology' of a protein by means of the HMMs of topology families of proteins. Then the most likely structural model for that protein is used to modify the sequence of secondary structure states previously obtained with a prediction algorithm. Our goal is to investigate the effect on thepmid:9322022 fatcat:yj6suh7zjfbxlmvhgrz4wvl2cm