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Issue 44, 2018
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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

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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.

Graphical abstract: 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

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Publication details

The article was received on 22 Mar 2018, accepted on 10 Oct 2018 and first published on 16 Oct 2018


Article type: Comment
DOI: 10.1039/C8NR02377H
Citation: Nanoscale, 2018,10, 20863-20866
  • Open access: Creative Commons BY license
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    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

    D. A. Tasi, J. Csontos, B. Nagy, Z. Kónya and G. Tasi, Nanoscale, 2018, 10, 20863
    DOI: 10.1039/C8NR02377H

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