Examining the predictive accuracy  of the novel 3D N‑linear algebraic molecular  codifications on benchmark datasets

García‑Jacas, César R.; Contreras‑Torres, Ernesto; Barigye, Stephen J.; Cabrera‑Leyva, Lisset

Examining the predictive accuracy of the novel 3D N‑linear algebraic molecular codifications on benchmark datasets

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Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.pdf (2.61 MB)

Date

2016

Authors

García‑Jacas, César R.

Contreras‑Torres, Ernesto

Barigye, Stephen J.

Cabrera‑Leyva, Lisset

Publisher

Journal of Cheminformatics

Abstract

Recently, novel 3D alignment-free molecular descriptors (also known as QuBiLS-MIDAS) based on two-linear, three-linear and four-linear algebraic forms have been introduced. These descriptors codify chemical information for relations between two, three and four atoms by using several (dis-)similarity metrics and multi-metrics. Several studies aimed at assessing the quality of these novel descriptors have been performed. However, a deeper analysis of their performance is necessary. Therefore, in the present manuscript an assessment and statistical validation of the performance of these novel descriptors in QSAR studies is performed.

Keywords

Multiple Linear Regression, QuBiLS-MIDAS, 3D-QSAR, TOMOCOMD-CARDD

Citation

García-Jacas, C. R., Contreras-Torres, E., Marrero-Ponce, Y., Pupo-Meriño, M., Barigye, S. J., & Cabrera-Leyva, L. (2016). Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets. Journal of Cheminformatics, 8, 1-16.https://doi.org/10.1186/s13321-016-0122-x

URI

https://nru.uncst.go.ug/handle/123456789/7672

Collections

Engineering and Technology

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