Random forest algorithm-based accurate prediction of rat acute oral toxicity-Reference-Cited by-同舟云学术

Random forest algorithm-based accurate prediction of rat acute oral toxicity

Published:2022-11-01 Issue:24 Volume:120 Page:
ISSN:0026-8976
Container-title:Molecular Physics
language:en
Short-container-title:Molecular Physics

Author:

Xiao Linrong¹,Deng Jiyong¹^ORCID,Yang Liping²,Huang Xianwei¹^ORCID,Yu Xinliang¹^ORCID

Affiliation:

1. Hunan Provincial Key Laboratory of Environmental Catalysis & Waste Regeneration, College of Materials and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, People’s Republic of China

2. Shenzhen Expressway Environment Co., Ltd., Shenzhen, People’s Republic of China

Funder

Open Project Program of Hunan Provincial Key Laboratory of Environmental Catalysis & Waste Regeneration

Publisher

Informa UK Limited

Subject

Physical and Theoretical Chemistry,Condensed Matter Physics,Molecular Biology,Biophysics

Link

https://www.tandfonline.com/doi/pdf/10.1080/00268976.2022.2140083

Reference42 articles.

1. Ecotoxicological QSAR modelling of organic chemicals against Pseudokirchneriella subcapitata using consensus predictions approach

2. High Throughput Heuristics for Prioritizing Human Exposure to Environmental Chemicals

3. Quantitative structure-toxicity relationships of organic chemicals against Pseudokirchneriella subcapitata

4. A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

5. Consensus QSAR modeling of toxicity of pharmaceuticals to different aquatic organisms: Ranking and prioritization of the DrugBank database compounds

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