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Assessment of Methods To Define the Applicability Domain of Structural Alert Models

https://doi.org/10.1021/ci1000967
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What this work says

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

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Approaches to Measure Chemical Similarity – a Review
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Use of structural alerts to develop rules for identifying chemical substances with skin irritation or skin corrosion potential
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Principles of QSAR models validation: internal and external
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Assessing Applicability Domains of Toxicological QSARs: Definition, Confidence in Predicted Values, and the Role of Mechanisms of Action
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Formation of Structural Categories to Allow for Read‐Across for Teratogenicity
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QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data
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Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity
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Atom pairs as molecular features in structure-activity studies: definition and applications
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A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models
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Model Selection Based on Structural Similarity−Method Description and Application to Water Solubility Prediction
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On Outliers and Activity CliffsWhy QSAR Often Disappoints
inferredcites →https://doi.org/10.1021/ci9000579openalex-snapshot
Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models
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On the Properties of Bit String-Based Measures of Chemical Similarity
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Derivation and Validation of Toxicophores for Mutagenicity Prediction
inferredcites →https://doi.org/10.1021/tx0497954openalex-snapshot
Structural AlertsA New Classification Model to Discriminate Excess Toxicity from Narcotic Effect Levels of Organic Compounds in the Acute Daphnid Assay
inferredcites →https://doi.org/10.1021/tx700212uopenalex-snapshot
Verification of the Structural Alerts for Michael Acceptors
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(Q)SAR S : gatekeepers against risk on chemicals?
inferredcites →https://doi.org/10.1080/10629360412331297362openalex-snapshot
The role of the European centre for the validation of alternative methods (ECVAM) in the validation of (Q)SARs
inferredcites →https://doi.org/10.1080/10629360701427872openalex-snapshot
An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential
inferredcites →https://doi.org/10.1080/10629360902949153openalex-snapshot
The physicochemical basis of QSARs for baseline toxicity
inferredcites →https://doi.org/10.1080/10659360500204426openalex-snapshot
Validity and validation of expert (Q)SAR systems
inferredcites →https://doi.org/10.1093/mutage/17.4.321openalex-snapshot
Comparison of the computer programs DEREK and TOPKAT to predict bacterial mutagenicity
inferredcites →https://doi.org/10.1177/026119290403200505openalex-snapshot
Development and Prevalidation of a List of Structure–Activity Relationship Rules to be Used in Expert Systems for Prediction of the Skin-sensitising Properties of Chemicals
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/10.1177/026119290503300508openalex-snapshot
QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review
inferredcites →https://doi.org/10.1177/026119290503300510openalex-snapshot
An Approach to Determining Applicability Domains for QSAR Group Contribution Models: An Analysis of SRC KOWWIN
inferredcites →https://doi.org/10.1177/026119290903700510openalex-snapshot
Definition of the Applicability Domains of Knowledge-based Predictive Toxicology Expert Systems by Using a Structural Fragment-based Approach
inferredcites →https://doi.org/10.1289/ehp.5758openalex-snapshot
Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
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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