A Quantitative Structure−Activity Relationships Model for the Acute Toxicity of Substituted Benzenes to Tetrahymena pyriformis Using Bayesian-Regularized Neural Networks-Reference-Cited by-同舟云学术

A Quantitative Structure−Activity Relationships Model for the Acute Toxicity of Substituted Benzenes to Tetrahymena pyriformis Using Bayesian-Regularized Neural Networks

Published:2000-05-18 Issue:6 Volume:13 Page:436-440
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Burden Frank R.¹,Winkler David A.²

Affiliation:

1. Chemistry Department, Monash University, Clayton, Victoria 3168, Australia

2. CSIRO Division of Molecular Science, Private Bag 10, Clayton South MDC, Clayton, Victoria 3169, Australia

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/tx9900627

Reference24 articles.

1. p-σ-π Analysis. A Method for the Correlation of Biological Activity and Chemical Structure

2. Using Artificial Neural Networks to Predict Biological Activity from Simple Molecular Structural Considerations

3. Goutte, C. (1997) Statistical Learning and Regularization for Regression. Ph.D. Thesis, University of Paris, Paris.

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