Work

Accurate Prediction of Rat Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hydrocarbon Derivatives Based on Chemometric QSAR and Machine Learning

Year: 2024

Type: article

Source: Environmental Science & Technology

DOI: 10.1021/acs.est.4c03966

Authors: Shuang Wu, Shi-Xin Li, Jing Qiu, Hai-Ming Zhao, Yan-Wen Li, Nai-Xian Feng, Bai-Lin Liu, Quan-Ying Cai, Lei Xiang, Ce-Hui Mo, Qing X. Li

Institutions: Jinan University, University of Hawaiʻi at Mānoa

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: U.S. Department of Agriculture, National Natural Science Foundation of China, Guangzhou Municipal Science and Technology Bureau, Fundamental Research Funds for the Central Universities, Science and Technology Planning Project of Guangdong Province, Basic and Applied Basic Research Foundation of Guangdong Province

Awards: G2899484271, G3513409932, G5463554858, G623606641, G7446846955, G7909957322, G8819088032, G984645195

OpenAlex ID: W4401534770

FWCI: 5.289

Cites: 61

Cited by: 27

Related to: 10