Several computational techniques are prominent in toxicology, including Quantitative Structure-Activity Relationship (QSAR) models, molecular docking, and machine learning algorithms. QSAR models predict the toxicity of chemicals based on their molecular structure. Molecular docking helps in understanding the interaction between chemicals and biological targets. Machine learning algorithms, on the other hand, can process vast datasets to identify patterns and predict toxicological outcomes.
