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Discovering Structural Alerts for Mutagenicity Using Stable Emerging Molecular Patterns

https://doi.org/10.1021/ci500611v
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What this work says

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

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Learning Closed Sets of Labeled Graphs for Chemical Applications
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Unsupervised Learning
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Scalable Estimates of Concept Stability
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Reducing the Representation Complexity of Lattice-Based Taxonomies
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On the Stimulation of Patterns
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Formal Concept Analysis
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On stability of a formal concept
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Extracting and summarizing the frequent emerging graph patterns from a dataset of graphs
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Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity
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Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP
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Computer prediction of possible toxic action from chemical structure: an update on the DEREK system
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Development of structure-activity relationship rules for predicting carcinogenic potential of chemicals
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Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products☆☆☆
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Computational toxicology in drug development
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The Gaston Tool for Frequent Subgraph Mining
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In silico toxicology for the pharmaceutical sciences☆
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Towards the creation of an international toxicology information centre
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Cellular, biochemical and genotoxic effects of inhaled mosquito repellent coil smoke in rodents
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Introduction to Lattices and Order
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HazardExpert
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Atom pairs as molecular features in structure-activity studies: definition and applications
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The Signature Molecular Descriptor. 1. Using Extended Valence Sequences in QSAR and QSPR Studies
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The Signature Molecular Descriptor. 2. Enumerating Molecules from Their Extended Valence Sequences
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Predictive Toxicology: Benchmarking Molecular Descriptors and Statistical Methods
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Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds
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Substructure Mining Using Elaborate Chemical Representation
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Introduction of Jumping Fragments in Combination with QSARs for the Assessment of Classification in Ecotoxicology
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ToxAlerts: A Web Server of Structural Alerts for Toxic Chemicals and Compounds with Potential Adverse Reactions
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Automating Knowledge Discovery for Toxicity Prediction Using Jumping Emerging Pattern Mining
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Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?
inferredcites →https://doi.org/10.1021/ci300400aopenalex-snapshot
In silico Prediction of Chemical Ames Mutagenicity
inferredcites →https://doi.org/10.1021/ci5001828openalex-snapshot
Emerging Pattern Mining To Aid Toxicological Knowledge Discovery
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Computational Derivation of Structural Alerts from Large Toxicology Data Sets
inferredcites →https://doi.org/10.1021/ci600301topenalex-snapshot
Emerging Chemical Patterns: A New Methodology for Molecular Classification and Compound Selection
inferredcites →https://doi.org/10.1021/ci900161gopenalex-snapshot
Benchmark Data Set for in Silico Prediction of Ames Mutagenicity
inferredcites →https://doi.org/10.1021/cr100222qopenalex-snapshot
Mechanisms of Chemical Carcinogenicity and Mutagenicity: A Review with Implications for Predictive Toxicology
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Artificial intelligence approach to structure-activity studies. Computer automated structure evaluation of biological activity of organic molecules
inferredcites →https://doi.org/10.1021/jm040835aopenalex-snapshot
Derivation and Validation of Toxicophores for Mutagenicity Prediction
inferredcites →https://doi.org/10.1023/a:1009796218281openalex-snapshot
Levelwise Search and Borders of Theories in Knowledge Discovery
inferredcites →https://doi.org/10.1038/npre.2011.6116openalex-snapshot
In-silico Predictive Mutagenicity Model Generation Using Supervised Learning Approaches
inferredcites →https://doi.org/10.1039/c4tx00071dopenalex-snapshot
New structural alerts for Ames mutagenicity discovered using emerging pattern mining techniques
inferredcites →https://doi.org/10.1073/pnas.70.3.782openalex-snapshot
An Improved Bacterial Test System for the Detection and Classification of Mutagens and Carcinogens
inferredcites →https://doi.org/10.1080/10629360902949179openalex-snapshot
Using chemical categories to fill data gaps in hazard assessment
inferredcites →https://doi.org/10.1093/bioinformatics/16.8.747openalex-snapshot
PASS: prediction of activity spectra for biologically active substances
inferredcites →https://doi.org/10.1093/bioinformatics/btg096openalex-snapshot
Toxicology analysis by means of the JSM-method
inferredcites →https://doi.org/10.1093/toxsci/kfm297openalex-snapshot
Computational Toxicology—A State of the Science Mini Review
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gSpan: graph-based substructure pattern mining
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Performance evaluation of the VF graph matching algorithm
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The European Commission's White Paper “Strategy for a Future Chemicals Policy”: A Review
inferredcites →https://doi.org/10.1142/s0129054108005735openalex-snapshot
ON SUCCINCT REPRESENTATION OF KNOWLEDGE COMMUNITY TAXONOMIES WITH FORMAL CONCEPT ANALYSIS
inferredcites →https://doi.org/10.1145/312129.312191openalex-snapshot
Efficient mining of emerging patterns
inferredcites →https://doi.org/10.1148/radiology.143.1.7063747openalex-snapshot
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
inferredcites →https://doi.org/10.1177/096032719101000405openalex-snapshot
Computer Prediction of Possible Toxic Action from Chemical Structure; The DEREK System
inferredcites →https://doi.org/10.1191/0960327105ht517oaopenalex-snapshot
Evidence-based toxicology: a comprehensive framework for causation
inferredcites →https://doi.org/10.1201/9780849350351.ch10openalex-snapshot
OncoLogic
inferredcites →https://doi.org/10.2174/138161207782794257openalex-snapshot
Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening
inferredcites →https://doi.org/10.2174/1568026013395074openalex-snapshot
Integration of Computational Analysis as a Sentinel Tool in Toxicological Assessments

What points at this work

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

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In SilicoPlatforms for Predictive Ecotoxicology
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