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Exact(8)
Therefore, the present manuscript introduces the QuBiLS-MAS (acronym for Quadratic, Bilinear and N-Linear mapS based on graph-theoretic electronic-density Matrices and Atomic weightingS) software designed to compute topological (0 2.5D) molecular descriptors based on bilinear, quadratic and linear algebraic forms for atom- and bond-based relations.
Novel molecular descriptors based on local spectral moments of the bond matrix are defined.
The descriptions of the 16 size-independent molecular descriptors based on the ratio of different molecular properties; Table S3.
In this report the predictive accuracy of the novel alignment-free geometric molecular descriptors based on N-linear algebraic maps (so called QuBiLS-MIDAS) has been examined.
Thus, we built a combined similarity index, where a fingerprint and 3 molecular descriptors based structural keys are combined with different weights.
Here, 16 molecular descriptors based on the ratio of different molecular properties (Additional file 1: Table S2 in the supporting materials) were examined.
Similar(52)
A new molecular descriptor based on partial charges is proposed.
It encodes a 3D molecule into a rotation-translation invariant molecular descriptor based on partial charges and inter-atomic distances.
Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching.
Although molecular descriptor based methods are computationally simple and effective in practice but they share several shortcomings most important being the inability to identify local similarity between structures.
Since then, steady progress has been observed in predictive toxicology, highly complemented by advances in cheminformatics approaches such as quantitative structure activity relationship (QSAR) modeling [9], physicochemical property and molecular descriptor based modeling [10, 11] and statistical methods [12].
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