Ivanduc, O., Ivanduc, T. Matrices and structural descriptors computed from molecular graph distances. In Topological Indices and Related Descriptors in QSAR and QSPR, Devillers, J. Balahan, A. T. (eds.), Gordon Breach, Amsterdam, 1999, pp. 221-277. [Pg.106]

O. Ivanciuc, T. Ivanciuc, and A.T. Balaban, Vertex- and edge-weighted molecular graphs and derived structural descriptors, in Topological indices and related descriptors in QSAR and QSPR, ed. J. Devillers and A.T. Balaban, Gordon Breach, Amsterdam, 1999, pp. 169-230. [Pg.109]

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One of the initial approaches to decrease these costs were attempted by correlating the biological function of a compound with its chemical structure, expressed in terms of molecular structural descriptors, by means of QSAR techniques. This discipline was promoted by Hansch and his group (Fujita, 1990). It was based on the determination of mathematical equations expressing the biological activities as a function of molecular parameters. [Pg.56]

All the techniques described above can be used to calculate molecular structures and energies. Which other properties are important for chemoinformatics Most applications have used semi-empirical theory to calculate properties or descriptors, but ab-initio and DFT are equally applicable. In the following, we describe some typical properties and descriptors that have been used in quantitative structure-activity (QSAR) and structure-property (QSPR) relationships. [Pg.390]

Clearly, the constant can be included into threshold value B, so that the function /o(C) = 1 is not necessary. We must stress that in such form the probabilistic approach has no tuned parameters at all. Some tuning of naive Bayes classifier can be performed by selection of the molecular structure descriptors [or /(C)] set. This is a wonderful feature in contrast to QSAR methods, especially to Artificial Neural Networks. [Pg.194]

See also in sourсe #XX -- [ Pg.26 ]

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