Development of a QSAR model to predict comedogenic potential of some cosmetic ingredients-Reference-Cited by-同舟云学术

Development of a QSAR model to predict comedogenic potential of some cosmetic ingredients

Published:2022-02 Issue: Volume:21 Page:100207
ISSN:2468-1113
Container-title:Computational Toxicology
language:en
Short-container-title:Computational Toxicology

Author:

Oztan Akturk Sebla,Tugcu Gulcin,Sipahi Hande

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Computer Science Applications,Toxicology

Reference113 articles.

1. Predicting students' performance using ID3 and C4.5 classification algorithms;Adhatrao;Int. J. Data Min. Knowl. Manag. Process,2013

2. J. Ali, R. Khan, A. Nasir, M. Imran (2012) Random forests and decision trees. Int J Comput Sci Issues 9:272–278. ISSN (Online): 1694-0814.

3. Alvascience-Srl (2019). alvaDesc (software for molecular descriptor calculation). v1.0.14, Italy. Available at: https://www.alvascience.com/, (Accessed June 10, 2021).

4. Oxidative stress and antioxidant strategies in dermatology;Baek;Redox Rep.,2016

5. Two-dimensional quantitative structure activity relationship models for 5alpha-reductase type 2 inhibitors;Balekundri;J. Pharm. Invest,2015

Cited by 3 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. Applications of Computational Toxicology in Pharmaceuticals, Environmental and Industrial Practices;Computational Toxicology for Drug Safety and a Sustainable Environment;2023-12-17

2. Integrating machine learning and high throughput screening for the discovery of allosteric AKT1 inhibitors;Journal of Biomolecular Structure and Dynamics;2023-12-14

3. A MULTIVARIATE INTERPOLATION APPROACH FOR PREDICTING DRUG LD50 VALUE;Ankara Universitesi Eczacilik Fakultesi Dergisi;2023-10-12