Quasi-SMILES-Based Nano-Quantitative Structure-Activity Relationship Model to Predict the Cytotoxicity of Multiwalled Carbon Nanotubes to Human Lung Cells.

No abstract is available for this paper.

• Publication year

  2018

• Venue

  Chemical Research in Toxicology

• Publication date

  2018-02-14

• Fields of study

  Medicine, Materials Science, Chemistry

• Identifiers
  DOI 10.1021/acs.chemrestox.7b00303PMID 29439565
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• CORAL and Nano-QFAR: Quantitative feature - Activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2).

  2017cited by this paper
• Nano-QSAR in cell biology: Model of cell viability as a mathematical function of available eclectic data.

  2017cited by this paper
• Monte Carlo–based quantitative structure–activity relationship models for toxicity of organic chemicals to Daphnia magna

  2016cited by this paper
• Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions.

  2016cited by this paper
• Evaluation of uptake, cytotoxicity and inflammatory effects in respiratory cells exposed to pristine and ‐OH and ‐COOH functionalized multi‐wall carbon nanotubes

  2016cited by this paper
• Meta-analysis of cellular toxicity for cadmium-containing quantum dots.

  2016cited by this paper
• Towards predicting the solubility of CO2 and N2 in different polymers using a quasi-SMILES based QSPR approach

  2016cited by this paper
• Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs

  2016cited by this paper
• QSAR model for predicting cell viability of human embryonic kidney cells exposed to SiO₂ nanoparticles.

  2016cited by this paper
• The Monte Carlo technique as a tool to predict LOAEL.

  2016cited by this paper
• Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions.

  2015cited by this paper
• Endocytosis of Multiwalled Carbon Nanotubes in Bronchial Epithelial and Mesothelial Cells

  2015cited by this paper
• Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes.

  2015cited by this paper
• QSAR as a random event: a case of NOAEL

  2015cited by this paper
• Monte Carlo Method‐Based QSAR Modeling of Penicillins Binding to Human Serum Proteins

  2015cited by this paper
• QSAR model as a random event: A case of rat toxicity.

  2015cited by this paper
• Optimal nano-descriptors as translators of eclectic data into prediction of the cell membrane damage by means of nano metal-oxides

  2014cited by this paper
• Physicochemical determinants of multiwalled carbon nanotubes on cellular toxicity: influence of a synthetic method and post-treatment.

  2014cited by this paper
• Free radical scavenging and formation by multi-walled carbon nanotubes in cell free conditions and in human bronchial epithelial cells

  2014cited by this paper
• A Meta‐Analysis of Carbon Nanotube Pulmonary Toxicity Studies—How Physical Dimensions and Impurities Affect the Toxicity of Carbon Nanotubes

  2014cited by this paper
• Inflammasome activation in airway epithelial cells after multi-walled carbon nanotube exposure mediates a profibrotic response in lung fibroblasts

  2014cited by this paper
• Differences in Cytotoxic, Genotoxic, and Inflammatory Response of Bronchial and Alveolar Human Lung Epithelial Cells to Pristine and COOH-Functionalized Multiwalled Carbon Nanotubes

  2014cited by this paper
• Potential Toxicity of Differential Functionalized Multiwalled Carbon Nanotubes (MWCNT) in Human Cell Line (BEAS2B) and Caenorhabditis elegans

  2014cited by this paper
• Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: the case of a group of ZnO and TiO2 nanoparticles.

  2014cited by this paper
• Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions.

  2014cited by this paper
• Modelling and predicting the biological effects of nanomaterials

  2014cited by this paper
• Predictive model development for adsorption of aromatic contaminants by multi-walled carbon nanotubes.

  2013cited by this paper
• Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO(2) nanoparticles.

  2013cited by this paper
• Development of structure-activity relationship for metal oxide nanoparticles.

  2013cited by this paper
• Culture medium type affects endocytosis of multi-walled carbon nanotubes in BEAS-2B cells and subsequent biological response.

  2013cited by this paper
• QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

  2013cited by this paper
• Nano-SAR development for bioactivity of nanoparticles with considerations of decision boundaries.

  2013cited by this paper
• SMILES‐Based QSAR Models for the Calcium Channel‐Antagonistic Effect of 1,4‐Dihydropyridines

  2013cited by this paper
• SMILES-based QSAR model for arylpiperazines as high-affinity 5-HT(1A) receptor ligands using CORAL.

  2013cited by this paper
• Classification NanoSAR development for cytotoxicity of metal oxide nanoparticles.

  2011cited by this paper
• Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles.

  2011cited by this paper
• Determination of Cytotoxicity Attributed to Multiwall Carbon Nanotubes (MWCNT) in Normal Human Embryonic Lung Cell (WI-38) Line

  2010cited by this paper
• SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes.

  2010cited by this paper
• Quantitative nanostructure-activity relationship modeling.

  2010cited by this paper
• QSAR modelling of carcinogenicity by balance of correlations

  2009cited by this paper
• ROS and NF-kappaB are involved in upregulation of IL-8 in A549 cells exposed to multi-walled carbon nanotubes.

  2009cited by this paper
• QSAR Modelling for Mutagenic Potency of Heteroaromatic Amines by Optimal SMILES‐based Descriptors

  2009cited by this paper
• Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships

  2005cited by this paper
• Hierarchical clustering schemes

  1967cited by this paper

• Simulation of the Impact of Pesticides on Pollinators Under Different Conditions Using Correlation Weighting of Quasi-SMILES Components Together with the Index of Ideality of Correlation (IIC)

  2026cites this paper
• Recent Advances in Machine Learning Models for Predicting Toxicity of Inorganic Nanoparticles

  2025cites this paper
• Chaos, Gambling, Simplicity: Simulation of nanoparticle delivery efficiency to organs of mice

  2025cites this paper
• Dynamic QSAR modeling for predicting in vivo genotoxicity and inflammation induced by nanoparticles and advanced materials: a time-dose-property/response approach

  2025cites this paper
• Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials

  2025influential citation
• A Comparative Review: Research in Safety and Sustainability of Carbon Nanomaterials Without and With Machine Learning Assistance

  2024influential citation
• A review on the structural characterization of nanomaterials for nano-QSAR models

  2024cites this paper
• De novo Design of Biocompatible Nanomaterials Using Quasi-SMILES and Recurrent Neural Networks.

  2024cites this paper
• In Vitro-to-In Vivo Extrapolation on Lung Toxicity Induced by Metal Oxide Nanoparticles via Data-Mining.

  2024cites this paper
• Machine Learning Models for Quantitatively Prediction of Toxicity in Macrophages Induced by Metal Oxide Nanoparticles.

  2024cites this paper
• Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials

  2024cites this paper
• Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation.

  2023cites this paper
• The system of self-consistent models based on quasi-SMILES as a tool to predict the potential of nano-inhibitors of human lung carcinoma cell line A549 for different experimental conditions

  2023cites this paper
• In Silico Simulation of Impacts of Metal Nano-Oxides on Cell Viability in THP-1 Cells Based on the Correlation Weights of the Fragments of Molecular Structures and Codes of Experimental Conditions Represented by Means of Quasi-SMILES

  2023cites this paper
• Human and environmental safety of carbon nanotubes across their life cycle

  2023cites this paper
• Toward Nano-Specific In Silico NAMs: How to Adjust Nano-QSAR to the Recent Advancements of Nanotoxicology?

  2023cites this paper
• Based on the Nano-QSAR model: Prediction of factors influencing damage to C. elegans caused by metal oxide nanomaterials and validation of toxic effects

  2023cites this paper
• A data reusability assessment in the nanosafety domain based on the NSDRA framework followed by an exploratory quantitative structure activity relationships (QSAR) modeling targeting cellular viability.

  2023cites this paper
• Development of Self-Consistency Models of Anticancer Activity of Nanoparticles under Different Experimental Conditions Using Quasi-SMILES Approach

  2023cites this paper
• Nanomaterials: Quasi-SMILES as a flexible basis for regulation and environmental risk assessment.

  2022cites this paper
• Use of quasi-SMILES to build models based on quantitative results from experiments with nanomaterials.

  2022cites this paper
• Structure-activity relationship of graphene-related materials: A meta-analysis based on mammalian in vitro toxicity data.

  2022cites this paper
• Quasi-SMILES as a basis to build up models of endpoints for nanomaterials

  2022cites this paper
• Machine Learning Models for Predicting Cytotoxicity of Nanomaterials.

  2022cites this paper
• Quasi-SMILES as a basis for the development of models for the toxicity of ZnO nanoparticles.

  2021cites this paper
• Status Quo in Data Availability and Predictive Models of Nano-Mixture Toxicity

  2021cites this paper
• Cytotoxicity of quantum dots: Use of quasiSMILES in development of reliable models with index of ideality of correlation and the consensus modelling.

  2021cites this paper
• Nano-QTTR development for interspecies aquatic toxicity of silver nanoparticles between daphnia and fish.

  2021cites this paper
• A Machine Learning Tool to Predict the Antibacterial Capacity of Nanoparticles

  2021cites this paper
• QSAR and machine learning modeling of toxicity of nanomaterials: a risk assessment approach

  2021cites this paper
• The System of Self-Consistent of Models: A New Approach to Build Up and Validation of Predictive Models of the Octanol/Water Partition Coefficient for Gold Nanoparticles

  2021cites this paper
• Unswerving modeling of hepatotoxicity of cadmium containing quantum dots using amalgamation of quasiSMILES, index of ideality of correlation, and consensus modeling

  2021cites this paper
• Health and environmental safety of nanomaterials: O Data, Where Art Thou?

  2021cites this paper
• Machine learning methods for multi-walled carbon nanotubes (MWCNT) genotoxicity prediction

  2021cites this paper
• Toward comprehension of the cytotoxicity of heterogeneous TiO2-based engineered nanoparticles: a nano-QSAR approach

  2021cites this paper
• Can the Monte Carlo method predict the toxicity of binary mixtures?

  2021cites this paper
• NanoTox: Development of a Parsimonious In Silico Model for Toxicity Assessment of Metal-Oxide Nanoparticles Using Physicochemical Features

  2021cites this paper
• Understanding Nanoparticle Toxicity to Direct a Safe-by-Design Approach in Cancer Nanomedicine

  2020cites this paper
• Practices and Trends of Machine Learning Application in Nanotoxicology

  2020influential citation
• The cytotoxicity of nanomaterials: Modeling multiple human cells uptake of functionalized magneto-fluorescent nanoparticles via nano-QSAR.

  2020cites this paper
• Nanotoxicology data for in silico tools: a literature review

  2020influential citation
• QSPR/QSAR: State-of-Art, Weirdness, the Future

  2020cites this paper
• The index of ideality of correlation: models of the flash points of ternary mixtures

  2020cites this paper
• Toxicity modelling of nanomaterials by origin evaluation of their physicochemical descriptors using a combination of principal component analysis and support vector machine methods

  2020cites this paper
• QSAR modeling of the toxicity classification of superparamagnetic iron oxide nanoparticles (SPIONs) in stem-cell monitoring applications: an integrated study from data curation to model development

  2020cites this paper
• QSAR without borders.

  2020cites this paper
• Correlation Intensity Index (CII) as a criterion of predictive potential: Applying to model thermal conductivity of metal oxide-based ethylene glycol nanofluids

  2020cites this paper
• Correlation intensity index: Building up models for mutagenicity of silver nanoparticles.

  2020cites this paper
• Artificial Intelligence and Machine Learning in Computational Nanotoxicology: Unlocking and Empowering Nanomedicine

  2020cites this paper
• Natural Ergot Alkaloids in Ocular Pharmacotherapy: Known Molecules for Novel Nanoparticle-Based Delivery Systems

  2020cites this paper
• Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning

  2020cites this paper
• Fullerenes C60 and C70: a model for solubility by applying the correlation intensity index

  2020cites this paper
• Correlation intensity index: mathematical modeling of cytotoxicity of metal oxide nanoparticles

  2020cites this paper
• Structure-activity prediction networks (SAPNets): a step beyond Nano-QSAR for effective implementation of the safe-by-design concept.

  2020cites this paper
• Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data

  2020influential citation
• Advancement of predictive modeling of zeta potentials (ζ) in metal oxide nanoparticles with correlation intensity index (CII)

  2020cites this paper
• Extending of QSPR/QSAR-algorithms for the prediction of the behavior of nanomaterials

  2020influential citation
• Review of aquatic toxicity of pharmaceuticals and personal care products to algae.

  2020cites this paper
• Toxicity of Carbon Nanotubes: Molecular Mechanisms, Signaling Cascades, and Remedies in Biomedical Applications.

  2020cites this paper
• Nanosafety

  2020cites this paper
• The Monte Carlo Method as a tool to build up predictive QSPR/QSAR.

  2019cites this paper
• A Safe‐by‐Design Strategy towards Safer Nanomaterials in Nanomedicines

  2019cites this paper
• In silico design of diacylglycerol acyltransferase-1 (DGAT1) inhibitors based on SMILES descriptors using Monte-Carlo method

  2019cites this paper
• Applying of the Monte Carlo method for the prediction of behavior of peptides.

  2019cites this paper
• Quasi-QSAR for predicting the cell viability of human lung and skin cells exposed to different metal oxide nanomaterials.

  2019cites this paper
• Importance of Choosing Relevant Biological End Points To Predict Nanoparticle Toxicity with Computational Approaches for Human Health Risk Assessment.

  2019cites this paper
• QSAR as a random event: criteria of predictive potential for a chance model

  2019cites this paper
• The Correlation Contradictions Index (CCI): Building up reliable models of mutagenic potential of silver nanoparticles under different conditions using quasi-SMILES.

  2019cites this paper
• Nano-(Q)SAR for Cytotoxicity Prediction of Engineered Nanomaterials

  2019cites this paper
• QSPR and nano-QSPR: What is the difference?

  2019cites this paper
• QSPR as a random event: solubility of fullerenes C[60] and C[70]

  2019cites this paper
• The index of ideality of correlation: models for flammability of binary liquid mixtures

  2019cites this paper
• Semi-correlations combined with the index of ideality of correlation: a tool to build up model of mutagenic potential

  2018cites this paper
• Nanobiotechnology: 1D nanomaterial building blocks for cellular interfaces and hybrid tissues

  2018cites this paper
• Quasi-SMILES as a tool to predict removal rates of pharmaceuticals and dyes in sewage

  2018cites this paper
• QSAR Models for Nitrogen Containing Monophosphonate and Bisphosphonate Derivatives as Human Farnesyl Pyrophosphate Synthase Inhibitors Based on Monte Carlo Method

  2018cites this paper
• Curation of datasets, assessment of their quality and completeness, and nanoSAR classification model development for metallic nanoparticles

  2018cites this paper
• MitoTarget Modeling Using ANN-Classification Models Based on Fractal SEM Nano-Descriptors: Carbon Nanotubes as Mitochondrial F0F1-ATPase Inhibitors.

  2018cites this paper
• Virtual Screening of Anti-Cancer Compounds: Application of Monte Carlo Technique.

  2018cites this paper
• Quasi-SMILES: quantitative structure–activity relationships to predict anticancer activity

  2018cites this paper
• Multivariate statistical analysis for selecting optimal descriptors in the toxicity modeling of nanomaterials

  2018cites this paper