QSAR in Toxicology: Methodological Foundations and Computational Workflows
Year: 2025
Type: article
Abstract: This methodological guide provides a comprehensive overview of data-driven approaches to Quantitative Structure–Activity Relationship (QSAR) modeling in toxicology. It introduces fundamental and advanced methods for data curation, descriptor generation, unsupervised and supervised learning, validation, applicability domain (AD) analysis, and model interpretation. Emphasis is placed on reproducible research, mechanistic interpretation, and regulatory alignment. The material integrates theoretical background with practical exercises and reproducible workflows implemented in modern computational environments.
Author: Muratov, Viacheslav
Institution: University of Gdańsk
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7085810554
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