title: An eigenvalue-eigenvector approach to predicting protein folding types.
abstract: The accuracy of predicting protein folding types can be significantly enhanced by a recently developed algorithm in which the coupling effect among different amino acid components is taken into account [Chou and Zhang (1994) J. Biol. Chem. 269, 22014-22020]. However, in practical calculations using this powerful algorithm, one may sometimes face ill-conditioned matrices. To overcome such a difficulty, an effective eigenvalue-eigenvector approach is proposed. Furthermore, the new approach has been used to predict a recently constructed set of 76 proteins not included in the training set, and the accuracy of prediction is also much higher than those of other methods.
authors.affiliation: Department of Physics, Tianjin University, China.
authors.forename: C T
authors.initials: CT
authors.lastname: Zhang
authors.forename: K C
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D008432:Mathematical Computing; D008969:Molecular Sequence Data; D011237:Predictive Value of Tests; D017510:Protein Folding; D017433:Protein Structure, Secondary