journal article·2018Open access

Comment on “Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models” by N. Sizochenko, A. Gajewicz, J. Leszczynski and T. Puzyn, Nanoscale , 2016, 8, 7203

Domonkos Attila Tasi, József Csontos, Balázs Nagy, Zoltán Kónya, Gyula Tasi

Nanoscale· Volume 10· Issue 44

Abstract

In this comment we show that the accuracy of a recent nano-QSAR model for toxicity predictions of metal oxide nanoparticles towards bacteria E. coli can be greatly improved. On one hand, the experimental ionization energies of metal atoms could be substituted for the erroneous semi-empirically derived heat of formation values of metal ions as descriptors to construct a more reliable nano-QSAR model based on weighted linear least-squares fittings. On the other hand, if no experimental data is available, a model relying on ionization energy descriptors from quantum chemical calculations could also be used producing exactly the same toxicity values as the experimental model.
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Research context

OpenAlex topics: Machine Learning in Materials Science · Computational Drug Discovery Methods · Geochemistry and Geologic Mapping

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Physical Chemistry and Materials Science

University of Szeged

H-6720 Szeged

Hungary

Budapest University of Technology and Economics

H-1521 Budapest

Department of Applied and Environmental Chemistry

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