Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds-Reference-Cited by-同舟云学术

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Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds

Published:2024-07-11 Issue:34 Volume:31 Page:47220-47236
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Lv Xiudi,He Mei,Wei Jiajia,Li Qiang,Nie Fan,Shao Zhiguo,Wang Zhansheng,Tian Lei

Funder

PetroChina Innovation Foundation

Yangtze University

CNPC Scientific Research and Technology Development Programme

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11356-024-34016-z.pdf

Reference97 articles.

1. Abdel-Shafy HI, Mansour MSM (2016) A review on polycyclic aromatic hydrocarbons: source, environmental impact, effect on human health and remediation. Egypt J Pet 25(1):107–123. https://doi.org/10.1016/j.ejpe.2015.03.011

2. Adeniji SE, Uba S, Uzairu A (2020) Theoretical modeling for predicting the activities of some active compounds as potent inhibitors against Mycobacterium tuberculosis using GFA-MLR approach. J King Saud Univ Sci 32(1):575–586. https://doi.org/10.1016/j.jksus.2018.08.010

3. Aldenberg T, Slob W (1993) Confidence limits for hazardous concentrations based on logistically distributed NOEC toxicity data. Ecotox Environ Safe 25(1):48–63. https://doi.org/10.1006/eesa.1993.1006

4. Barzegar A, Jafari MS, Hamidi H, Sadeghi M (2017) 2D-QSAR study of fullerene nanostructure derivatives as potent HIV-1 protease inhibitors. Physica E Low Dimens Syst Nanostruct 93:324–331. https://doi.org/10.1016/j.physe.2017.06.016

5. Baumann D, Baumann K (2014) Reliable estimation of prediction errors for QSAR models under model uncertainty using double cross-validation. J Cheminf 6(1):47. https://doi.org/10.1186/s13321-014-0047-1

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