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Computational Prediction of the Chromosome-Damaging Potential of Chemicals
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Comparison of the results of a modified miniscreen and the standard bacterial reverse mutation assays
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Handbook of Molecular Descriptors
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Assessment of the sensitivity of the computational programs DEREK, TOPKAT, and MCASE in the prediction of the genotoxicity of pharmaceutical molecules
inferredcites →https://doi.org/10.1002/em.2850160304openalex-snapshot
Significant differences in the structural basis of the induction of sister chromatid exchanges and chromosomal aberrations in chinese hamster ovary cells
inferredcites →https://doi.org/10.1007/978-0-387-21606-5openalex-snapshot
The Elements of Statistical Learning
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Approaches to SAR in carcinogenesis and mutagenesis. Prediction of carcinogenicity/mutagenicity using MULTI-CASE
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Perspectives in mutation epidemiology: 3. Contribution of chromosome abnormalities to human morbidity and mortality and some comments upon surveillance of chromosome mutation rates
inferredcites →https://doi.org/10.1016/j.mrgentox.2003.12.010openalex-snapshot
SAR modeling of genotoxic phenomena: the consequence on predictive performance of deviation from a unity ratio of genotoxicants/non-genotoxicants
inferredcites →https://doi.org/10.1016/j.mrgentox.2005.02.004openalex-snapshot
Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens
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Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens
inferredcites →https://doi.org/10.1016/j.neucom.2005.12.136openalex-snapshot
Time series prediction with ensemble models applied to the CATS benchmark
inferredcites →https://doi.org/10.1016/j.tox.2005.08.019openalex-snapshot
Application of support vector machine (SVM) for prediction toxic activity of different data sets
inferredcites →https://doi.org/10.1016/j.tox.2006.04.032openalex-snapshot
Use of computer-assisted prediction of toxic effects of chemical substances
inferredcites →https://doi.org/10.1016/s0027-5107(02)00076-3openalex-snapshot
Chromosomal aberrations: formation, identification and distribution
inferredcites →https://doi.org/10.1016/s0169-409x(02)00012-1openalex-snapshot
Computer systems for the prediction of toxicity: an update
inferredcites →https://doi.org/10.1016/s1383-5718(03)00135-9openalex-snapshot
A multiple in silico program approach for the prediction of mutagenicity from chemical structure
inferredcites →https://doi.org/10.1016/s1383-5718(99)00175-8openalex-snapshot
Interpretation of the biological relevance of genotoxicity test results: the importance of thresholds
inferredcites →https://doi.org/10.1016/s1383-5742(01)00055-2openalex-snapshot
A review of the genotoxicity of marketed pharmaceuticals
inferredcites →https://doi.org/10.1016/s1383-5742(97)00030-6openalex-snapshot
Evaluation of the in vitro micronucleus test as an alternative to the in vitro chromosomal aberration assay: position of the GUM working group on the in vitro micronucleus test
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A Scoring Scheme for Discriminating between Drugs and Nondrugs
inferredcites →https://doi.org/10.1021/tx020077wopenalex-snapshot
Development of Binary Classification of Structural Chromosome Aberrations for a Diverse Set of Organic Compounds from Molecular Structure
inferredcites →https://doi.org/10.1021/tx030032aopenalex-snapshot
Predicting the Genotoxicity of Polycyclic Aromatic Compounds from Molecular Structure with Different Classifiers
inferredcites →https://doi.org/10.1021/tx049652hopenalex-snapshot
Prediction of Genotoxicity of Chemical Compounds by Statistical Learning Methods
inferredcites →https://doi.org/10.1038/271452a0openalex-snapshot
Does carcinogenic potency correlate with mutagenic potency in the Ames assay?
inferredcites →https://doi.org/10.1080/10629360290002055openalex-snapshot
AI and SAR approaches for predicting chemical carcinogenicity: Survey and status report
inferredcites →https://doi.org/10.1080/10629369908039181openalex-snapshot
Development, Characterization and Application of Predictive-Toxicology Models
inferredcites →https://doi.org/10.1093/mutage/17.6.509openalex-snapshot
Detection and characterization of mechanisms of action of aneugenic chemicals
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Classification And Regression Trees
inferredcites →https://doi.org/10.1214/aos/1024691079openalex-snapshot
Arcing classifier (with discussion and a rejoinder by the author)
inferredcites →https://doi.org/10.2174/1568011043352920openalex-snapshot
Chromosomal Aberrations and Genomic Instability Induced by Topoisomerase- Targeted Antitumour Drugs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Reflections on the origins and evolution of genetic toxicology and the environmental mutagen society
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Computational chemistry approach for the early detection of drug‐induced idiosyncratic liver toxicity
inferred← citeshttps://doi.org/10.1007/978-1-4419-0197-2_2openalex-snapshot
(Q)SAR Models for Genotoxicity Assessment
inferred← citeshttps://doi.org/10.1007/978-3-540-92203-2_9openalex-snapshot
Ensemble Modeling for Bio-medical Applications
inferred← citeshttps://doi.org/10.1016/b978-0-12-809252-1.00010-9openalex-snapshot
Mutagenicity Testing
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Artificial intelligence in space
inferred← citeshttps://doi.org/10.1016/j.sjbs.2018.05.013openalex-snapshot
CORAL: Building up QSAR models for the chromosome aberration test
inferred← citeshttps://doi.org/10.1016/j.toxlet.2020.04.016openalex-snapshot
New QSAR models to predict chromosome damaging potential based on the in vivo micronucleus test
inferred← citeshttps://doi.org/10.1016/j.yrtph.2018.09.026openalex-snapshot
Construction and application of (Q)SAR models to predict chemical-induced in vitro chromosome aberrations
inferred← citeshttps://doi.org/10.1016/j.yrtph.2019.104427openalex-snapshot
Integrated in silico and in vitro genotoxicity assessment of thirteen data-poor substances
inferred← citeshttps://doi.org/10.1021/ci900367jopenalex-snapshot
A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test
inferred← citeshttps://doi.org/10.1021/tx700249qopenalex-snapshot
Identifying the Structural Requirements for Chromosomal Aberration by Incorporating Molecular Flexibility and Metabolic Activation of Chemicals
inferred← citeshttps://doi.org/10.1080/02652030903233231openalex-snapshot
Risk assessment of food-contact materials: past experience and future challenges
inferred← citeshttps://doi.org/10.1093/mutage/gey017openalex-snapshot
In silico prediction of chromosome damage: comparison of three (Q)SAR models
inferred← citeshttps://doi.org/10.1109/fbit.2007.38openalex-snapshot
Early Detection of Prostate Cancer with Classifier Ensembles
inferred← citeshttps://doi.org/10.1109/ijcnn.2007.4371418openalex-snapshot
Agnostic Learning with Ensembles of Classifiers
inferred← citeshttps://doi.org/10.1155/2008/218097openalex-snapshot
Classification Models for Early Detection of Prostate Cancer
inferred← citeshttps://doi.org/10.1201/9781420008326.ch10openalex-snapshot
Carcinogenicity and Mutagenicity Testing In Vivo
inferred← citeshttps://doi.org/10.1201/9781420008326.ch15openalex-snapshot
Mutagenicity Testing In Vitro
inferred← citeshttps://doi.org/10.1201/b15319-18openalex-snapshot
Carcinogenicity and mutagenicity testing in vivo
inferred← citeshttps://doi.org/10.14279/depositonce-2052openalex-snapshot
Machine Learning Methods for Life Sciences: Intelligent Data Analysis in Bio- and Chemoinformatics
inferred← citeshttps://doi.org/10.2174/156802607782194725openalex-snapshot
Computational Techniques in Fragment Based Drug Discovery
inferred← citeshttps://doi.org/10.3109/15376516.2014.881946openalex-snapshot
SAR genotoxicity and tumorigenicity predictions for 2-MI and 4-MI using multiple SAR software
inferred← citeshttps://doi.org/10.3390/cells12010040openalex-snapshot
Human Health during Space Travel: State-of-the-Art Review
inferred← citeshttps://doi.org/10.3390/genes11101181openalex-snapshot
In Silico Model for Chemical-Induced Chromosomal Damages Elucidates Mode of Action and Irrelevant Positives
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