title: Protein secondary structure prediction.
abstract: The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family. New techniques that apply machine learning and discriminant analysis show promise as alternatives to neural networks.
authors.affiliation: Laboratory of Molecular Biophysics, Oxford, UK.
authors.forename: G J
authors.initials: GJ
authors.lastname: Barton
mesh_terms: D000818:Animals; D006801:Humans; D011237:Predictive Value of Tests; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D017421:Sequence Analysis
chemical_list: D011506:Proteins