Boyd, Eds., VCH Publishers, New York, 1991, Vol. 2, pp. 367-422. The Molecular Connectivity Chi Indexes and Kappa Shape Indexes in Structure-Property Modeling. I. B. Bersuker and A. S. Dimoglo, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1991, Vol. 2, pp. 423 60. The Electron-Topological Approach to the QSAR Problem. [Pg.252]

This concept could be extended to any other linear and nonlinear QSAR relationships, by calculating either n x n distance matrices D (especially suited for nonlinear relationships) or n X n covariance matrices C as similarity measures. For this purpose, all or only several relevant properties of the compounds are used to calculate the corresponding similarity matrices. No superposition of the molecules is necessary. If a distance matrix D is calculated from the X matrix of explanatory physicochemical properties n rows, m columns), then all Xij values must be normalized before, i.e., mean-value-centered and standardized, column by column. The great advantage of distance similarity index matrices is that no special models need to be defined in the case of nonlinear relationships on the other hand, problems may arise from significant intercorrelations between the different columns of the similarity matrices. [Pg.2319]

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