A Kernel-Based Method for Assessing Uncertainty on Individual QSAR Predictions-Reference-Cited by-同舟云学术

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A Kernel-Based Method for Assessing Uncertainty on Individual QSAR Predictions

Published:2012-09-25 Issue:10 Volume:31 Page:741-751
ISSN:1868-1743
Container-title:Molecular Informatics
language:en
Short-container-title:Mol. Inf.

Author:

Tebby Cleo,Mombelli Enrico

Funder

French Ministry in Charge of Ecology and Sustainable Development

Publisher

Wiley

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,Molecular Medicine,Structural Biology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/minf.201200053/fullpdf

Reference29 articles.

1. A Risk Assessment Perspective of Current Practice in Characterizing Uncertainties in QSAR Regression Predictions

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

3. Assessing the reliability of a QSAR model's predictions

4. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modelling Structure Activity Landscapes with Cliffs: a Kernel Regression-Based Approach;Molecular Informatics;2013-07

2. Perspectives for integrating human and environmental risk assessment and synergies with socio-economic analysis;Science of The Total Environment;2013-07

3. Uncertainty in QSAR Predictions;Alternatives to Laboratory Animals;2013-03

4. Arguments for considering Uncertainty in QSAR Predictions in Hazard and Risk Assessments;Alternatives to Laboratory Animals;2013-03

5. Interpretable, Probability-Based Confidence Metric for Continuous Quantitative Structure–Activity Relationship Models;Journal of Chemical Information and Modeling;2013-02-05

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