Abstract
In the absence of crystallographic data, many structural features of proteins can be deduced from the analysis of protein sequences. One of the most promising tools for the near future relates to the prediction of antigenic sites (for a review, see Berzofsky, 1985; Delisi and Berzofsky, 1985; Margalit et al., 1987) for the engineering of synthetic vaccines. In addition, with the increasing number of protein sequences known from DNA cloning and sequencing, the need for a theoretical treatment of protein sequences has never been greater. In this context, many different methods for predicting the secondary structure of proteins have been developed (Finkelstein and Ptitsyn, 1971; Robson and Pain, 1971; Kabat and Wu, 1973; Burgess et al., Chou and Fasman, 1974; Lim, 1974; Nagano, 1977; Garnier et al., 1978; Cid et al., 1982). Several of these methods are statistical i.e., they are based on the observed frequency with which individual residues are found in given structural states.
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© 1989 Plenum Press, New York
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Deléage, G., Roux, B. (1989). Use of Class Prediction to Improve Protein Secondary Structure Prediction. In: Fasman, G.D. (eds) Prediction of Protein Structure and the Principles of Protein Conformation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1571-1_13
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DOI: https://doi.org/10.1007/978-1-4613-1571-1_13
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