An eigenvalue-eigenvector approach to predicting protein folding types |
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Authors: | Chun-Ting Zhang and Kuo-Chen Chou |
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Institution: | (1) Department of Physics, Tianjin University, Tianjin, China;(2) Computer-Aided Drug Discovery, Upjohn Laboratories, 49007-4940 Kalamazoo, Michigan |
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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 illconditioned 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. |
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Keywords: | Amino acid composition 20D space covariance matrix Mahalanobis distance |
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