ArticleScientific reports2018
Toxicity Classification of Oxide Nanomaterials: Effects of Data Gap Filling and PChem Score-based Screening Approaches.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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Who cites it
22 citing papers in PubMed.
- Review on Predictive Models and Integration Strategies for Holistic Impact Assessment of Chemicals and Materials.Environmental science & technology · 2026Review
- Automated Large-Scale Extraction of Nanotoxicity Data from the Literature Using Multimodal Large Language Models.Computational and structural biotechnology journal · 2026Article
- Recent Advances in Machine Learning Models for Predicting Toxicity of Inorganic Nanoparticles.Chem & bio engineering · 2025Review
- Dynamic QSAR modeling for predicting in vivo genotoxicity and inflammation induced by nanoparticles and advanced materials: a time-dose-property/response approach.Journal of nanobiotechnology · 2025Article
- AI-based nanotoxicity data extraction and prediction of nanotoxicity.Computational and structural biotechnology journal · 2025Article
- Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance.Computational and structural biotechnology journal · 2024Article
- Nanotechnology in retinal diseases: From disease diagnosis to therapeutic applications.Biophysics reviews · 2024Review
- Experimental and Computational Nanotoxicology-Complementary Approaches for Nanomaterial Hazard Assessment.Nanomaterials (Basel, Switzerland) · 2022Review
- Merging data curation and machine learning to improve nanomedicines.Advanced drug delivery reviews · 2022Review
- Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.Nature plants · 2021Review
- NanoTox: Development of a ParsimoniousACS omega · 2021Article
- Current Strategies in Assessment of Nanotoxicity: Alternatives to In Vivo Animal Testing.International journal of molecular sciences · 2021Review
- Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data.Nanomaterials (Basel, Switzerland) · 2020Article
- Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform.Nanomaterials (Basel, Switzerland) · 2020Article
- Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.International journal of molecular sciences · 2020Article
- QSAR without borders.Chemical Society reviews · 2020Review
- Article
- Practices and Trends of Machine Learning Application in Nanotoxicology.Nanomaterials (Basel, Switzerland) · 2020Review
- NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools forComputational and structural biotechnology journal · 2020Review
- A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform.Nanoscale advances · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Development of nanotoxicity prediction models is becoming increasingly important in the risk assessment of engineered nanomaterials. However, it has significant obstacles caused by the wide heterogeneities of published literature in terms of data completeness and quality. Here, we performed a meta-analysis of 216 published articles on oxide nanoparticles using 14 attributes of physicochemical, toxicological and quantum-mechanical properties. Particularly, to improve completeness and quality of the extracted dataset, we adapted two preprocessing approaches: data gap-filling and physicochemical property based scoring. Performances of nano-SAR classification models revealed that the dataset with the highest score value resulted in the best predictivity with compromise in its applicability domain. The combination of physicochemical and toxicological attributes was proved to be more relevant to toxicity classification than quantum-mechanical attributes. Overall, by adapting these two preprocessing methods, we demonstrated that meta-analysis of nanotoxicity literatures could provide an effective alternative for the risk assessment of engineered nanomaterials.
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Registered trials
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