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Multispecies QSAR Modeling for Predicting the Aquatic Toxicity of Diverse Organic Chemicals for Regulatory Toxicology

https://doi.org/10.1021/tx400371w
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Toxicity of 58 substituted anilines and phenols to algae Pseudokirchneriella subcapitata and bacteria Vibrio fischeri: Comparison with published data and QSARs
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Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches
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Toxicity and quantitative structure–activity relationships of benzoic acids to Pseudokirchneriella subcapitata
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QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants
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Daphnia and fish toxicity of (benzo)triazoles: Validated QSAR models, and interspecies quantitative activity–activity modelling
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Consistency of random survival forests
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Estimating the toxicities of organic chemicals to bioluminescent bacteria and activated sludge
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Use of QSAR models in predicting joint effects in multi-component mixtures of organic chemicals
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QSAR study on the toxicity of substituted benzenes to the algae (Scenedesmus obliquus)
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Quantitative structure-activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspecies correlation with Tetrahymena pyriformis
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Stochastic gradient boosting
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Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient
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Comments on the Definition of the Q 2 Parameter for QSAR Validation
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Development of Binary Classification of Structural Chromosome Aberrations for a Diverse Set of Organic Compounds from Molecular Structure
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Assessment and Modeling of the Toxicity of Organic Chemicals to Chlorella vulgaris: Development of a Novel Database
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Classification of the Carcinogenicity of N-Nitroso Compounds Based on Support Vector Machines and Linear Discriminant Analysis
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Top-Priority Fragment QSAR Approach in Predicting Pesticide Aquatic Toxicity
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Quantitative Structure−Activity Analysis of the Algae Toxicity of Nitroaromatic Compounds
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Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles
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Toxic equivalent concentrations (TEQs) for baseline toxicity and specific modes of action as a tool to improve interpretation of ecotoxicity testing of environmental samples
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Quantitative Nanostructure–Activity Relationship modelling of nanoparticles
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QSARs for toxicity to the bacteriumSinorhizobium meliloti
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An Approach to Determining Applicability Domains for QSAR Group Contribution Models: An Analysis of SRC KOWWIN
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New public QSAR model for carcinogenicity
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Mechanisms of General Anesthesia
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Correlations of Vibrio fischeri Bacteria Test Data with Bioassay Data for Other Organisms
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Test No 201 Alga Growth Inhibition Test
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Test No. 202: Daphnia sp. Acute Immobilisation Test
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Test No. 203: Fish, Acute Toxicity Test
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A comparison of model performance for six quantitative structure-activity relationship packages that predict acute toxicity to fish
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Quantitative structure-activity relationships for toxicity of nonpolar narcotic chemicals to Pseudokirchneriella subcapitata
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PREDICTION OF THE AQUATIC TOXICITY OF PHENOLS TO TETRAHYMENA PYRIFORMIS FROM MOLECULAR DESCRIPTORS
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The activity against methicillin-resistant Staphylococcus aureus and quantitative structure-activity relationship (QSAR) study of aza-naphthindolizinedione derivatives

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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BFGTP: A BERT-Guided Two-Stage Molecular Representation Learning Framework for Toxicity Prediction
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Systems Biology and Synthetic Biology: A New Epoch for Toxicology Research
inferred← citeshttps://doi.org/10.1177/0261192920986811openalex-snapshot
The Implementation of the Three Rs in Regulatory Toxicity and Biosafety Assessment: The Indian Perspective
inferred← citeshttps://doi.org/10.26686/wgtn.17012312openalex-snapshot
Molecular evolution and functional characterisation of tunicate xenobiotic receptors
inferred← citeshttps://doi.org/10.3390/molecules26226983openalex-snapshot
New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
inferred← citeshttps://doi.org/10.3390/toxics14060498openalex-snapshot
QSAR Modeling to Predict Aquatic Toxicity Across Multiple Species
inferred← citeshttps://doi.org/10.3390/toxics9100261openalex-snapshot
Environmental Risk Assessment of Vehicle Exhaust Particles on Aquatic Organisms of Different Trophic Levels
inferred← citeshttps://doi.org/10.4018/ijqspr.2017010106openalex-snapshot
In Silico Strategy for Diagnosis of Chronic Kidney Disease
inferred← citeshttps://doi.org/10.4018/ijqspr.20201001.oa2openalex-snapshot
Development of Generalized QSAR Models for Predicting Cytotoxicity and Genotoxicity of Metal Oxides Nanoparticles
inferred← citeshttps://doi.org/10.48130/newcontam-0026-0010openalex-snapshot
Toxicity prediction and ecological risk assessment of new contaminants to rare and endangered species using machine learning-QSAR: a case study of conserving Gobiocypris rarus in the Yangtze River Basin
inferred← citeshttps://doi.org/10.70675/41b22f7az01dcz48abzaa5ez4d3ae90798c7openalex-snapshot
Comprehensive data analysis and predictive chemoinformatics models for REACH related physicochemical and (eco)toxicity properties
inferred← citeshttps://doi.org/10.7759/s44388-025-03407-4openalex-snapshot
Effect of Fe Doping on Dye Degradation of Calcium Titanate
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