A QSAR study for predicting malformation in zebrafish embryo
Author:
Affiliation:
1. Department of Comparative Bioscience, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
2. Computer Science Department, York University, Toronto, Canada
Funder
Research Center of Toxicology
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/15376516.2024.2338907
Reference39 articles.
1. The Utility of Structure–Activity Relationship (SAR) Models for Prediction and Covariate Selection in Developmental Toxicity: Comparative Analysis of Logistic Regression and Decision Tree Models
2. Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints
3. In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity
4. A comparative analysis of gradient boosting algorithms
5. The Zebrafish Embryo as a Model Organism for Testing mRNA-Based Therapeutics
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