Results 11 to 20 of about 82,891 (271)

In silico toxicological risk assessment of chemical constituents from Curtisia dentata stem-bark extract [PDF]

Toxicology Reports
Herbal products are widely used in healthcare due to their therapeutic potential. However, concerns persist among medicinal chemists and regulatory toxicologists regarding their safety and potential toxicity.
Anna S. van Wyk, Olusesan Ojo, Olusola Bodede, Gerhard Prinsloo   +3 more
doaj   +2 more sources

Corrigendum: In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts [PDF]

Frontiers in Chemistry, 2018
Hongbin Yang, Lixia Sun, Weihua Li, Guixia Liu, Yun Tang   +4 more
doaj   +2 more sources

Machine Learning for Predicting Risk of Drug-Induced Autoimmune Diseases by Structural Alerts and Daily Dose [PDF]

International Journal of Environmental Research and Public Health, 2021
Yue Wu, Peter P Fu, Huixiao Hong
exaly   +2 more sources

Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay [PDF]

Journal of Hazardous Materials, 2022
Xuelian Jia, Xia Wen, Daniel P Russo
exaly   +2 more sources

Using Machine Learning Methods and Structural Alerts for Prediction of Mitochondrial Toxicity [PDF]

Molecular Informatics, 2020
Jennifer Hemmerich, Gerhard F Ecker
exaly   +2 more sources

Machine Learning-based Classification for the Prioritization of Potentially Hazardous Chemicals with Structural Alerts in Nontarget Screening [PDF]

Environmental Science & Technology
Nienke Meekel, Anneli Kruve, Marja H Lamoree   +2 more
exaly   +2 more sources

Modeling and insights into the structural basis of chemical acute aquatic toxicity

Ecotoxicology and Environmental Safety, 2022
It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce
Ruiqiu Zhang, Huizhu Guo, Yuqing Hua, Xueyan Cui, Yinping Shi, Xiao Li   +5 more
doaj   +1 more source

Development of Prediction Models for Drug-Induced Cholestasis, Cirrhosis, Hepatitis, and Steatosis Based on Drug and Drug Metabolite Structures

Frontiers in Pharmacology, 2020
Drug-induced liver injury (DILI) is one of the major reasons for termination of drug development. Due to the importance of predicting DILI in early phases of drug development, diverse in silico models have been developed to filter out DILI-causing ...
Hyun Kil Shin, Myung-Gyun Kang, Daeui Park, Daeui Park, Tamina Park, Tamina Park, Seokjoo Yoon, Seokjoo Yoon   +7 more
doaj   +1 more source

Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity

Computational and Structural Biotechnology Journal, 2012
The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity ...
Natalja Fjodorova, Marjana Novič
doaj   +3 more sources

In Silico Prediction and Insights Into the Structural Basis of Drug Induced Nephrotoxicity

Frontiers in Pharmacology, 2022
Drug induced nephrotoxicity is a major clinical challenge, and it is always associated with higher costs for the pharmaceutical industry and due to detection during the late stages of drug development.
Yinping Shi, Yuqing Hua, Yuqing Hua, Baobao Wang, Ruiqiu Zhang, Ruiqiu Zhang, Xiao Li, Xiao Li   +7 more
doaj   +1 more source