| Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms N Golbamaki, B Rasulev, A Cassano, RLM Robinson, E Benfenati, ... Nanoscale 7 (6), 2154-2198, 2015 | 210 | 2015 |
| Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction T Ferrari, D Cattaneo, G Gini, N Golbamaki Bakhtyari, A Manganaro, ... SAR and QSAR in Environmental Research 24 (5), 365-383, 2013 | 140 | 2013 |
| Comparison of in silico models for prediction of mutagenicity NG Bakhtyari, G Raitano, E Benfenati, T Martin, D Young Journal of Environmental Science and Health, Part C 31 (1), 45-66, 2013 | 98 | 2013 |
| A solid-phase extraction procedure coupled to 1H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey G Beretta, E Caneva, L Regazzoni, NG Bakhtyari, RM Facino Analytica chimica acta 620 (1-2), 176-182, 2008 | 71 | 2008 |
| Mining toxicity structural alerts from SMILES: A new way to derive Structure Activity Relationships T Ferrari, G Gini, NG Bakhtyari, E Benfenati 2011 IEEE symposium on computational intelligence and data mining (CIDM …, 2011 | 40 | 2011 |
| 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 |
| New clues on carcinogenicity-related substructures derived from mining two large datasets of chemical compounds A Golbamaki, E Benfenati, N Golbamaki, A Manganaro, E Merdivan, ... Journal of Environmental Science and Health, Part C 34 (2), 97-113, 2016 | 27 | 2016 |
| Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action SE Escher, A Aguayo-Orozco, E Benfenati, A Bitsch, T Braunbeck, ... Toxicology in Vitro 79, 105269, 2022 | 17 | 2022 |
| Compilation of data and modelling of nanoparticle interactions and toxicity in the NanoPUZZLES Project AN Richarz, A Avramopoulos, E Benfenati, A Gajewicz, ... Modelling the Toxicity of Nanoparticles, 303-324, 2017 | 17 | 2017 |
| High-throughput analysis of ovarian cycle disruption by mixtures of aromatase inhibitors FY Bois, N Golbamaki-Bakhtyari, S Kovarich, C Tebby, HA Gabb, ... Environmental Health Perspectives 125 (7), 077012, 2017 | 13 | 2017 |
| Classification nano-SAR modeling of metal oxides nanoparticles genotoxicity based on comet assay data A Golbamaki, N Golbamaki, N Sizochenko, B Rasulev, A Cassano, ... 52. Congress of the European Societies of Toxicology (EUROTOX 2016) 258 …, 2016 | 3 | 2016 |
| Genotoxicity of metal oxide nanoparticles: a new predictive (Q) SAR model NG Bakhtyari, B Rasulev, J Leszczynski, E Benfenati, M Cronin Environmental and Molecular Mutagenesis 54, S48-S48, 2013 | 3 | 2013 |
| Toxicological and ecotoxicological studies for additives NG Bakhtyari, D Baderna, E Boriani, M Schuhmacher, S Heise, ... Global Risk-Based Management of Chemical Additives II: Risk-Based Assessment …, 2013 | 2 | 2013 |
| P17-20 New approach methodologies for the teratogenic potential of cosmetics: building an ITS M Burbank, F Gautier, A Noel-Voisin, T Wildemann, N Golbamaki, A Riu, ... Toxicology Letters 368, S234-S235, 2022 | | 2022 |
| High throughput modeling of the effects of mixtures of ToxCast chemicals on steroid hormone cycles in women FY Bois, N Golbamaki, S Kovarich, E Lemazurier ISES 2016 Annual Meeting, 173, 2016 | | 2016 |
| Toxicological Characterization of Waste-Related Products Using Alternative Methods: Three Case Studies D Baderna, N Golbamaki, S Maggioni, M Vaccari, A Colacci, E Benfenati Global Risk-Based Management of Chemical Additives II: Risk-Based Assessment …, 2013 | | 2013 |
| Deliverable Report S MIZAR | | |
Jerzy LeszczynskiProfessor of Chemistry and President's Distinguished Fellow, Jackson State UniversityVerified email at icnanotox.org
