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Open AccessJournal ArticleDOI

Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.

TLDR
This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs.
Abstract
This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs. Useful diagnostic tools and data analytical approaches are highlighted and exemplified. Particular emphasis is given to the question of how to define the applicability borders of a QSAR and how to estimate parameter and prediction uncertainty. The article ends with a discussion regarding QSAR acceptability criteria. This discussion contains a list of recommended acceptability criteria, and we give reference values for important QSAR performance statistics. Finally, we emphasize that rigorous and independent validation of QSARs is an essential step toward their regulatory acceptance and implementation.

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Citations
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Journal ArticleDOI

Principles of QSAR models validation: internal and external

TL;DR: Evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.
Journal ArticleDOI

Best Practices for QSAR Model Development, Validation, and Exploitation.

TL;DR: Most critical QSAR modeling routines that are regarded as best practices in the field are examined, including procedures used to validate models, both internally and externally, as well as the need to define model applicability domains that should be used when models are employed for the prediction of external compounds or compound libraries.
Journal ArticleDOI

Matrix metalloproteinases (MMPs): Chemical–biological functions and (Q)SARs

TL;DR: An attempt has been made to explore the in-depth knowledge from the classification of this enzyme to the clinical trials of their inhibitors, and QSAR results on the inhibition of various compound series against MMP-1 reveal a number of interesting points.
Journal ArticleDOI

Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles

TL;DR: A model is developed to describe the cytotoxicity of 17 different types of metal oxide nanoparticles to bacteria Escherichia coli that reliably predicts the toxicity of all considered compounds, and the methodology is expected to provide guidance for the future design of safe nanomaterials.
References
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Book

An introduction to the bootstrap

TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Book

Applied Regression Analysis

TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
Book

Genetic Algorithms

Book

The jackknife, the bootstrap, and other resampling plans

Bradley Efron
TL;DR: The Delta Method and the Influence Function Cross-Validation, Jackknife and Bootstrap Balanced Repeated Replication (half-sampling) Random Subsampling Nonparametric Confidence Intervals as mentioned in this paper.
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