title: An object programming based environment for protein secondary structure prediction.
abstract: The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.
authors.affiliation: Department of Computer, Communication and System Sciences, University of Genoa, Italy.
authors.forename: M
authors.initials: M
authors.lastname: Giacomini
authors.forename: C
authors.initials: C
authors.lastname: Ruggiero
authors.forename: R
authors.initials: R
authors.lastname: Sacile
mesh_terms: D000595:Amino Acid Sequence; D016208:Databases, Factual; D006860:Hydrogen Bonding; D008958:Models, Molecular; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000145:classification; D015203:Reproducibility of Results; D012984:Software
chemical_list: D011506:Proteins