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Estimation of Carcinogenicity Using Molecular Fragments Tree

https://doi.org/10.1021/ci300266p
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Searches for ultimate chemical carcinogens and their reactions with cellular macromolecules
inferredcites →https://doi.org/10.1002/em.2860070613openalex-snapshot
Fundamental structural alerts to potential carcinogenicity or noncarcinogenicity
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Carcinogenicity of analgesics: Long‐term treatment of sprague‐dawley rats with phenacetin, phenazone, caffeine and paracetamol (acetamidophen)
inferredcites →https://doi.org/10.1007/s11030-005-9001-5openalex-snapshot
Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity
inferredcites →https://doi.org/10.1016/0165-1218(88)90114-0openalex-snapshot
Chemical structure, Salmonella mutagenicity and extent of carcinogenicity as indicators of genotoxic carcinogenesis among 222 chemicals tested in rodents by the U.S. NCI/NTP
inferredcites →https://doi.org/10.1016/j.addr.2006.10.008openalex-snapshot
Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products☆☆☆
inferredcites →https://doi.org/10.1016/j.mrrev.2008.05.003openalex-snapshot
Structure alerts for carcinogenicity, and the Salmonella assay system: A novel insight through the chemical relational databases technology
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/s1383-5742(01)00055-2openalex-snapshot
A review of the genotoxicity of marketed pharmaceuticals
inferredcites →https://doi.org/10.1021/ci034254qopenalex-snapshot
Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds
inferredcites →https://doi.org/10.1021/ci0503715openalex-snapshot
Substructure Mining Using Elaborate Chemical Representation
inferredcites →https://doi.org/10.1021/cr100222qopenalex-snapshot
Mechanisms of Chemical Carcinogenicity and Mutagenicity: A Review with Implications for Predictive Toxicology
inferredcites →https://doi.org/10.1021/cr941192hopenalex-snapshot
A Critical Appraisal of the Evolution ofN-Nitrosoureas as Anticancer Drugs
inferredcites →https://doi.org/10.1021/jm0004594openalex-snapshot
Toward the Design of Chemical Libraries for Mass Screening Biased against Mutagenic Compounds
inferredcites →https://doi.org/10.1021/jm040835aopenalex-snapshot
Derivation and Validation of Toxicophores for Mutagenicity Prediction
inferredcites →https://doi.org/10.1021/tx700336nopenalex-snapshot
Quantitative Structure−Carcinogenicity Relationship for Detecting Structural Alerts in Nitroso Compounds: Species, Rat; Sex, Female; Route of Administration, Gavage
inferredcites →https://doi.org/10.1093/carcin/19.1.147openalex-snapshot
Contribution of hydrazines-derived alkyl radicals to cytotoxicity and transformation induced in normal c-myc-overexpressing mouse fibroblasts
inferredcites →https://doi.org/10.1093/toxsci/67.1.38openalex-snapshot
Diethanolamine Induces Hepatic Choline Deficiency in Mice
inferredcites →https://doi.org/10.1145/1014052.1014134openalex-snapshot
A quickstart in frequent structure mining can make a difference
inferredcites →https://doi.org/10.1145/502512.502533openalex-snapshot
Molecular feature mining in HIV data
inferredcites →https://doi.org/10.2174/0929867013373084openalex-snapshot
Mechanisms of Carcinogenesis Focus on Oxidative Stress and Electron Transfer

What points at this work

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

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Machine Learning-Based Modeling of Drug Toxicity
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Identification of Structural Alerts by Machine Learning and Their Applications in Toxicology
inferred← citeshttps://doi.org/10.1016/j.bbagen.2016.05.015openalex-snapshot
Analysis of the chemical toxicity effects using the enrichment of Gene Ontology terms and KEGG pathways
inferred← citeshttps://doi.org/10.1016/j.fct.2019.110921openalex-snapshot
CapsCarcino: A novel sparse data deep learning tool for predicting carcinogens
inferred← citeshttps://doi.org/10.1021/acs.chemrestox.0c00006openalex-snapshot
Computational Approaches to Identify Structural Alerts and Their Applications in Environmental Toxicology and Drug Discovery
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00198openalex-snapshot
Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis
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Stereodivergent Synthesis of Alkenylpyridines via Pd/Cu Catalyzed C–H Alkenylation of Pyridinium Salts with Alkynes
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ortho -Selective C–H Alkenylation of Pyridines Enabled by a Heterometallic Mg–Ni–Mg Complex
inferred← citeshttps://doi.org/10.1038/ncomms6676openalex-snapshot
A chemo-centric view of human health and disease
inferred← citeshttps://doi.org/10.1039/c5mb00276aopenalex-snapshot
A computational method for the identification of new candidate carcinogenic and non-carcinogenic chemicals
inferred← citeshttps://doi.org/10.1155/2015/246374openalex-snapshot
Identification of Chemical Toxicity Using Ontology Information of Chemicals
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Integration of bioinformatics to biodegradation
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Predicting Chemical Toxicity Effects Based on Chemical-Chemical Interactions
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Finding Candidate Drugs for Hepatitis C Based on Chemical-Chemical and Chemical-Protein Interactions
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SApredictor: An Expert System for Screening Chemicals Against Structural Alerts
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