Predicting Carcinogenicity of Polycyclic Aromatic Hydrocarbons from Back-Propagation Neural Network-Reference-Cited by-同舟云学术

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Predicting Carcinogenicity of Polycyclic Aromatic Hydrocarbons from Back-Propagation Neural Network

Published:1994-11-01 Issue:6 Volume:34 Page:1288-1293
ISSN:0095-2338
Container-title:Journal of Chemical Information and Computer Sciences
language:en
Short-container-title:J. Chem. Inf. Comput. Sci.

Author:

Villemin Didier,Cherqaoui Driss,Mesbah Abdelhalim

Publisher

American Chemical Society (ACS)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci00022a010

Cited by 42 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. Systematic QSAR and iQCCR modelling of fused/non-fused aromatic hydrocarbons (FNFAHs) carcinogenicity to rodents: reducing unnecessary chemical synthesis and animal testing;Green Chemistry;2022

2. Current contamination status of traditional and emerging persistent toxic substances in the sediments of Ulsan Bay, South Korea;Marine Pollution Bulletin;2020-11

3. Research Progress of Gaseous Polycyclic Aromatic Hydrocarbons Purification by Adsorption;Aerosol and Air Quality Research;2019

4. Machine Learning Methods in Computational Toxicology;Methods in Molecular Biology;2018

5. Predicting carcinogenicity of organic compounds based on CPDB;Chemosphere;2015-11

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