| review article | Q7318358 |
| scholarly article | Q13442814 |
| P50 | author | Martina G Vijver | Q57204484 |
| P2093 | author name string | Guangchao Chen | |
| Willie Peijnenburg | |||
| Yinlong Xiao | |||
| P2860 | cites work | Surface charge-dependent toxicity of silver nanoparticles | Q82747608 |
| Effect of morphology of ZnO nanostructures on their toxicity to marine algae | Q83486741 | ||
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| Nano-QSAR modeling for predicting biological activity of diverse nanomaterials | Q92086023 | ||
| The use of ionization potentials Part 1. Ionic radii of the elements | Q112073849 | ||
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| Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information | Q28530221 | ||
| Dissolution of silver nanowires and nanospheres dictates their toxicity to Escherichia coli | Q30393162 | ||
| Developing species sensitivity distributions for metallic nanomaterials considering the characteristics of nanomaterials, experimental conditions, and different types of endpoints | Q30491360 | ||
| Using experimental data of Escherichia coli to develop a QSAR model for predicting the photo-induced cytotoxicity of metal oxide nanoparticles | Q30722652 | ||
| Summary and analysis of the currently existing literature data on metal-based nanoparticles published for selected aquatic organisms: Applicability for toxicity prediction by (Q)SARs. | Q30993824 | ||
| Classification NanoSAR development for cytotoxicity of metal oxide nanoparticles | Q33859712 | ||
| Surface-Charge-Dependent Cell Localization and Cytotoxicity of Cerium Oxide Nanoparticles | Q34163805 | ||
| What is computational toxicology? | Q34301624 | ||
| NanoE-Tox: New and in-depth database concerning ecotoxicity of nanomaterials | Q36082067 | ||
| Probabilistic modelling of prospective environmental concentrations of gold nanoparticles from medical applications as a basis for risk assessment | Q36398030 | ||
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| Toxicity of Ag, CuO and ZnO nanoparticles to selected environmentally relevant test organisms and mammalian cells in vitro: a critical review. | Q36917097 | ||
| Computational toxicology--a state of the science mini review | Q37027100 | ||
| A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping). | Q38394202 | ||
| Dose metrics assessment for differently shaped and sized metal-based nanoparticles. | Q38790333 | ||
| Linear and non-linear modelling of the cytotoxicity of TiO2 and ZnO nanoparticles by empirical descriptors. | Q38838799 | ||
| Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs. | Q38852385 | ||
| Case studies putting the decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping) into practice | Q38929969 | ||
| Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions. | Q38941508 | ||
| Computer-aided nanotoxicology: assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel QSTR-perturbation approach. | Q38969588 | ||
| Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies | Q38979118 | ||
| Development of structure-activity relationship for metal oxide nanoparticles | Q39149585 | ||
| Are engineered nano iron oxide particles safe? an environmental risk assessment by probabilistic exposure, effects and risk modeling | Q39249392 | ||
| Modeling biological activities of nanoparticles | Q39265233 | ||
| Parametrization of nanoparticles: development of full-particle nanodescriptors. | Q39314325 | ||
| Toxicity of silver nanoparticles - nanoparticle or silver ion? | Q39440086 | ||
| Surface charge of gold nanoparticles mediates mechanism of toxicity | Q39608532 | ||
| Comparative study of predictive computational models for nanoparticle-induced cytotoxicity | Q39691029 | ||
| Combining exposure and effect modeling into an integrated probabilistic environmental risk assessment for nanoparticles. | Q39793947 | ||
| Probabilistic modeling of the flows and environmental risks of nano-silica | Q40129232 | ||
| Multispecies toxicity test for silver nanoparticles to derive hazardous concentration based on species sensitivity distribution for the protection of aquatic ecosystems. | Q40244428 | ||
| Probabilistic environmental risk assessment of five nanomaterials (nano-TiO2, nano-Ag, nano-ZnO, CNT, and fullerenes). | Q40337620 | ||
| Species sensitivity weighted distribution for ecological risk assessment of engineered nanomaterials: the n-TiO2 case study. | Q40853274 | ||
| Aquatic acute species sensitivity distributions of ZnO and CuO nanoparticles | Q40987562 | ||
| Species sensitivity distributions for engineered nanomaterials | Q41071451 | ||
| Novel approach for efficient predictions properties of large pool of nanomaterials based on limited set of species: nano-read-across | Q41728796 | ||
| Concepts of nanoparticle dose metric and response metric | Q42746509 | ||
| Predictive modeling of nanomaterial exposure effects in biological systems. | Q42957668 | ||
| Engineered nanomaterials in water and soils: a risk quantification based on probabilistic exposure and effect modeling | Q43355043 | ||
| Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles | Q43415971 | ||
| Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach | Q43630055 | ||
| Conducting a battery of bioassays for gold nanoparticles to derive guideline value for the protection of aquatic ecosystems. | Q46872044 | ||
| Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli | Q47615270 | ||
| Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression. | Q51040052 | ||
| From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles. | Q54279902 | ||
| Causal inference methods to assist in mechanistic interpretation of classification nano-SAR models | Q56999520 | ||
| Addressing a bottle neck for regulation of nanomaterials: quantitative read-across (Nano-QRA) algorithm for cases when only limited data is available | Q57008772 | ||
| Comparative Aquatic Toxicity of Gold Nanoparticles and Ionic Gold Using a Species Sensitivity Distribution Approach | Q58847614 | ||
| Development of nanostructure–activity relationships assisting the nanomaterial hazard categorization for risk assessment and regulatory decision-making | Q60477142 | ||
| Particle-specific toxic effects of differently shaped zinc oxide nanoparticles to zebrafish embryos (Danio rerio ) | Q60477155 | ||
| P275 | copyright license | Creative Commons Attribution | Q6905323 |
| P433 | issue | 7 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | toxicology | Q7218 |
| nanomaterial | Q967847 | ||
| environment | Q2249676 | ||
| manufactured product | Q3406743 | ||
| P577 | publication date | 2017-07-12 | |
| P1433 | published in | International Journal of Molecular Sciences | Q3153277 |
| P859 | sponsor | Framework to respond to regulatory needs of future nanomaterials and markets | Q55095480 |
| P1476 | title | Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials | |
| P478 | volume | 18 |
| Q55312176 | Carbon Nanotubes and Other Engineered Nanoparticles Induced Pathophysiology on Mesothelial Cells and Mesothelial Membranes. |
| Q63284221 | How to judge whether QSAR/read-across predictions can be trusted: a novel approach for establishing a model's applicability domain |
| Q89274889 | Multiscale Coupling Strategy for Nano Ecotoxicology Prediction |
| Q47639565 | Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology |
| Q99412763 | Prediction of the Joint Toxicity of Multiple Engineered Nanoparticles: The Integration of Classic Mixture Models and In Silico Methods |
| Q52584444 | Risk Assessment and Risk Minimization in Nanomedicine: A Need for Predictive, Alternative, and 3Rs Strategies. |
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