| From basic physics to mechanisms of toxicity: The “liquid drop” approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles N Sizochenko, B Rasulev, A Gajewicz, V Kuz'min, T Puzyn, J Leszczynski Nanoscale 6 (22), 13986-13993, 2014 | 106 | 2014 |
| How the toxicity of nanomaterials towards different species could be simultaneously evaluated: A novel multi-nano-read-across approach N Sizochenko, A Mikolajczyk, K Jagiello, T Puzyn, J Leszczynski, ... Nanoscale 10, 582-591, 2018 | 54 | 2018 |
| Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques N Sizochenko, M Syzochenko, N Fjodorova, B Rasulev, J Leszczynski Ecotoxicology and environmental safety 185, 109733, 2019 | 42 | 2019 |
| Chemoinformatics approach for characterization of hybrid nanomaterials: safer and efficient design perspective A Mikolajczyk, N Sizochenko, E Mulkiewicz, A Malankowska, B Rasulev, ... Nanoscale 11, 11808-11818, 2019 | 42 | 2019 |
| Rutin as promising drug for the treatment of Parkinson’s disease: an assessment of MAO-B inhibitory potential by docking, molecular dynamics and DFT studies F Azam, HS Abodabos, IM Taban, AR Rfieda, D Mahmood, MJ Anwar, ... Molecular Simulation 45 (18), 1563-1571, 2019 | 37 | 2019 |
| Zeta potentials (ζ) of metal oxide nanoparticles: A meta-analysis of experimental data and predictive neural networks modeling N Sizochenko, A Mikolajczyk, M Syzochenko, T Puzyn, J Leszczynski NanoImpact 22, 100317, 2021 | 36 | 2021 |
| Towards the development of global nano-quantitative structure–property relationship models: zeta potentials of metal oxide nanoparticles AA Toropov, N Sizochenko, AP Toropova, J Leszczynski Nanomaterials 8 (4), 243, 2018 | 34 | 2018 |
| In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study A Gooch, N Sizochenko, B Rasulev, L Gorb, J Leszczynski Environmental Toxicology and Chemistry 36 (8), 2227–2233, 2017 | 34 | 2017 |
| Evaluating the toxicity of TiO2-based nanoparticles to Chinese hamster ovary cells and Escherichia coli: A complementary experimental and computational approach A Mikolajczyk, N Sizochenko, E Mulkiewicz, A Malankowska, M Nischk, ... Beilstein Journal of Nanotechnology 8, 2171, 2017 | 30 | 2017 |
| Quantitative structure-property relationship model leading to virtual screening of fullerene derivatives: Exploring structural attributes critical for photoconversion … S Kar, N Sizochenko, L Ahmed, VS Batista, J Leszczynski Nano Energy 26, 677-691, 2016 | 30 | 2016 |
| Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models N Sizochenko, A Gajewicz, J Leszczynski, T Puzyn Nanoscale 8 (13), 7203-7208, 2016 | 29 | 2016 |
| Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties A Golbamaki, N Golbamaki, N Sizochenko, B Rasulev, J Leszczynski, ... Nanotoxicology 12 (10), 1113-1129, 2018 | 28 | 2018 |
| Review of current and emerging approaches for quantitative nanostructure-activity relationship modeling: The case of inorganic nanoparticles N Sizochenko, J Leszczynski Journal of Nanotoxicology and Nanomedicine 1 (1), 1-16, 2016 | 26 | 2016 |
| Predicting physical properties of nanofluids by computational modeling N Sizochenko, M Syzochenko, A Gajewicz, J Leszczynski, T Puzyn The Journal of Physical Chemistry C 121 (3), 1910–1917, 2017 | 25 | 2017 |
| A DFT-based QSAR study on inhibition of human dihydrofolate reductase S Karabulut, N Sizochenko, A Orhan, J Leszczynski Journal of Molecular Graphics and Modelling 70, 23-29, 2016 | 25 | 2016 |
| Modeling of interactions between the zebrafish hatching enzyme ZHE1 and a series of metal oxide nanoparticles: nano-QSAR and causal analysis of inactivation mechanisms N Sizochenko, D Leszczynska, J Leszczynski Nanomaterials 7 (10), 330, 2017 | 22 | 2017 |
| Causal inference methods to assist in mechanistic interpretation of classification nano-SAR models N Sizochenko, B Rasulev, A Gajewicz, E Mokshyna, VE Kuz'min, ... RSC Advances 5 (95), 77739-77745, 2015 | 22 | 2015 |
| How the “liquid drop” approach could be efficiently applied for quantitative structure–property relationship modeling of nanofluids N Sizochenko, K Jagiello, J Leszczynski, T Puzyn The Journal of Physical Chemistry C 119 (45), 25542-25547, 2015 | 21 | 2015 |
| Using quasi-SMILES for the predictive modeling of the safety of 574 metal oxide nanoparticles measured in different experimental conditions AP Toropova, AA Toropov, J Leszczynski, N Sizochenko Environmental Toxicology and Pharmacology 86, 103665, 2021 | 19 | 2021 |
| Advancement of predictive modeling of zeta potentials (ζ) in metal oxide nanoparticles with correlation intensity index (CII) AA Toropov, N Sizochenko, AP Toropova, D Leszczynska, J Leszczynski Journal of Molecular Liquids 317, 113929, 2020 | 18 | 2020 |
Jerzy LeszczynskiProfessor of Chemistry and President's Distinguished Fellow, Jackson State UniversityVerified email at icnanotox.org
