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Merging Applicability Domains for in Silico Assessment of Chemical Mutagenicity
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-0258(19961015)15:19<2121::aid-sim346>3.0.co;2-mopenalex-snapshot
CLINICAL BIOSTATISTICS. AN INTRODUCTION TO EVIDENCE BASED MEDICINE.
inferredcites →https://doi.org/10.1007/978-1-60761-839-3_5openalex-snapshot
Similarity Searching Using 2D Structural Fingerprints
inferredcites →https://doi.org/10.1016/j.yrtph.2005.04.006openalex-snapshot
The use of structure–activity relationship analysis in the food contact notification program
inferredcites →https://doi.org/10.1016/j.yrtph.2013.05.001openalex-snapshot
Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities
inferredcites →https://doi.org/10.1016/s0027-5107(00)00064-6openalex-snapshot
The Ames Salmonella/microsome mutagenicity assay
inferredcites →https://doi.org/10.1021/ci034160gopenalex-snapshot
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
inferredcites →https://doi.org/10.1021/ci049782wopenalex-snapshot
Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR
inferredcites →https://doi.org/10.1021/ci1000899openalex-snapshot
Benchmark Performance of MultiCASE Inc. Software in Ames Mutagenicity Set
inferredcites →https://doi.org/10.1021/ci700372sopenalex-snapshot
Using Molecular Fingerprint as Descriptors in the QSPR Study of Lipophilicity
inferredcites →https://doi.org/10.1021/ci800024copenalex-snapshot
Scores of Extended Connectivity Fingerprint as Descriptors in QSPR Study of Melting Point and Aqueous Solubility
inferredcites →https://doi.org/10.1021/ci900161gopenalex-snapshot
Benchmark Data Set for in Silico Prediction of Ames Mutagenicity
inferredcites →https://doi.org/10.1021/tx300279fopenalex-snapshot
Locally Weighted Learning Methods for Predicting Dose-Dependent Toxicity with Application to the Human Maximum Recommended Daily Dose
inferredcites →https://doi.org/10.1038/clpt.2011.300openalex-snapshot
(Q)SAR Modeling and Safety Assessment in Regulatory Review
inferredcites →https://doi.org/10.1039/b409865jopenalex-snapshot
Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures
inferredcites →https://doi.org/10.1073/pnas.70.8.2281openalex-snapshot
Carcinogens are Mutagens: A Simple Test System Combining Liver Homogenates for Activation and Bacteria for Detection
inferredcites →https://doi.org/10.1093/mutage/5.4.333openalex-snapshot
Structural alerts to genotoxicity: the interaction of human and artificial intelligence
inferredcites →https://doi.org/10.1093/mutage/gep017openalex-snapshot
Comparison of the Ames II and traditional Ames test responses with respect to mutagenicity, strain specificities, need for metabolism and correlation with rodent carcinogenicity
inferredcites →https://doi.org/10.1111/j.1365-2125.1994.tb05705.xopenalex-snapshot
International conference on harmonisation of technical requirements for registration of pharmaceuticals for human use (ICH).
inferredcites →https://doi.org/10.1177/026119290503300209openalex-snapshot
Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships
inferredcites →https://doi.org/10.1186/1758-2946-5-26openalex-snapshot
Open-source platform to benchmark fingerprints for ligand-based virtual screening
inferredcites →https://doi.org/10.1517/17425255.2012.724059openalex-snapshot
Latest advances in computational genotoxicity prediction
inferredcites →https://doi.org/10.3390/molecules17054791openalex-snapshot
Comparison of Different Approaches to Define the Applicability Domain of QSAR Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Reliability and Applicability Assessment for Machine Learning Models
inferred← citeshttps://doi.org/10.1007/s10910-018-0855-zopenalex-snapshot
An ensemble approach for in silico prediction of Ames mutagenicity
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Current and emerging new approach & methodologies for skin hazard assessment
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Prioritization of mycotoxins based on mutagenicity and carcinogenicity evaluation using combined in silico QSAR methods
inferred← citeshttps://doi.org/10.1016/j.jwpe.2026.110655openalex-snapshot
Oxidation byproducts in advanced water treatment: Formation mechanisms, toxicity attribution, and risk-oriented assessment
inferred← citeshttps://doi.org/10.1016/j.molstruc.2022.134093openalex-snapshot
Dihydroquercetin (DHQ) has the potential to promote apoptosis in ovarian cancer cells: An in silico and in vitro study
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2025.112735openalex-snapshot
QSAR modeling and Monte Carlo simulations of aldehyde derivatives as corrosion inhibitors for mild steel in hydrochloric acid medium
inferred← citeshttps://doi.org/10.1016/j.tox.2023.153676openalex-snapshot
Development of a read-across-derived classification model for the predictions of mutagenicity data and its comparison with traditional QSAR models and expert systems
inferred← citeshttps://doi.org/10.1016/j.yrtph.2015.01.010openalex-snapshot
An evaluation of in-house and off-the-shelf in silico models: Implications on guidance for mutagenicity assessment
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00110openalex-snapshot
The Relative Importance of Domain Applicability Metrics for Estimating Prediction Errors in QSAR Varies with Training Set Diversity
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00255openalex-snapshot
Critically Assessing the Predictive Power of QSAR Models for Human Liver Microsomal Stability
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00616openalex-snapshot
General Purpose 2D and 3D Similarity Approach to Identify hERG Blockers
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00281openalex-snapshot
Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00264openalex-snapshot
Building of Robust and Interpretable QSAR Classification Models by Means of the Rivality Index
inferred← citeshttps://doi.org/10.1039/9781782622659-00185openalex-snapshot
The Need for a Green Electronic Lab Notebook
inferred← citeshttps://doi.org/10.1039/d4me00038bopenalex-snapshot
Applying local interpretable model-agnostic explanations to identify substructures that are responsible for mutagenicity of chemical compounds
inferred← citeshttps://doi.org/10.1080/10590501.2017.1391521openalex-snapshot
Integrating computational methods to predict mutagenicity of aromatic azo compounds
inferred← citeshttps://doi.org/10.1080/1062936x.2019.1644666openalex-snapshot
Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain
inferred← citeshttps://doi.org/10.1093/toxsci/kfw125openalex-snapshot
New Quantitative Structure–Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds
inferred← citeshttps://doi.org/10.1101/2022.08.11.503624openalex-snapshot
Merging Bioactivity Predictions from Cell Morphology and Chemical Fingerprint Models Using Similarity to Training Data
inferred← citeshttps://doi.org/10.1186/1758-2946-6-20openalex-snapshot
Supervised extensions of chemography approaches: case studies of chemical liabilities assessment
inferred← citeshttps://doi.org/10.1186/s13321-016-0173-zopenalex-snapshot
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability
inferred← citeshttps://doi.org/10.1186/s13321-023-00723-xopenalex-snapshot
Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
inferred← citeshttps://doi.org/10.1517/17460441.2016.1117070openalex-snapshot
An overview of molecular fingerprint similarity search in virtual screening
inferred← citeshttps://doi.org/10.22270/jddt.v12i1.5179openalex-snapshot
In-silico ADMET profile of Ellagic Acid from Syzygium cumini: A Natural Biaryl Polyphenol with Therapeutic Potential to Overcome Diabetic Associated Vascular Complications
inferred← citeshttps://doi.org/10.22270/jddt.v12i2-s.5286openalex-snapshot
ADME-Tox profile of Cuminaldehyde (4-Isopropylbenzaldehyde) from Cuminum cyminum seeds for potential biomedical applications
inferred← citeshttps://doi.org/10.22270/jddt.v12i2-s.5289openalex-snapshot
In-silico Absorption, Distribution, Metabolism, Elimination and Toxicity profile of 9,12,15-Octadecatrienoic acid (ODA) from Moringa oleifera
inferred← citeshttps://doi.org/10.22270/jddt.v12i3.5352openalex-snapshot
In silico Target Class Prediction and Probabilities for Plant Derived Omega 3 Fatty Acid from Ethyl Acetate Fraction of Moringa oleifera Leaf Extract
inferred← citeshttps://doi.org/10.22270/jddt.v12i4-s.5533openalex-snapshot
ADMET informatics of Tetradecanoic acid (Myristic Acid) from ethyl acetate fraction of Moringa oleifera leaves
inferred← citeshttps://doi.org/10.22270/jddt.v12i5.5605openalex-snapshot
ADMET informatics of Plant Derived n-Hexadecanoic Acid (Palmitic Acid) from ethyl acetate fraction of Moringa oleifera leaf extract
inferred← citeshttps://doi.org/10.22270/jddt.v12i5.5654openalex-snapshot
ADMET-informatics, Pharmacokinetics, Drug-likeness and Medicinal Chemistry of Bioactive Compounds of Physalis minima Ethanolic Leaf Extract (PMELE) as a Potential Source of Natural Lead Molecules for Next Generation Drug Design, Development and Therapies
inferred← citeshttps://doi.org/10.3389/fphar.2017.00889openalex-snapshot
vNN Web Server for ADMET Predictions
inferred← citeshttps://doi.org/10.3390/molecules23112756openalex-snapshot
Study of the Applicability Domain of the QSAR Classification Models by Means of the Rivality and Modelability Indexes
inferred← citeshttps://doi.org/10.6084/m9.figshare.26593592openalex-snapshot
Additional file 1 of Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
inferred← citeshttps://doi.org/10.6084/m9.figshare.26593595openalex-snapshot
Additional file 2 of Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
inferred← citeshttps://doi.org/10.6084/m9.figshare.26593598openalex-snapshot
Additional file 3 of Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
inferred← citeshttps://doi.org/10.6084/m9.figshare.26593601openalex-snapshot
Additional file 4 of Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
inferred← citeshttps://doi.org/10.6084/m9.figshare.26593604openalex-snapshot
Additional file 5 of Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data
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