3 Result(s)
within
Sundar Thangapandian
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Chapter
Quantitative Target-specific Toxicity Prediction Modeling (QTTPM): Coupling Machine Learning with Dynamic Protein–Ligand Interaction Descriptors (DyPLIDs) to Predict Androgen Receptor-mediated Toxicity
Ligand-based quantitative structure–activity relationship modeling often lacks the dynamic and mechanistic insights of target–chemical interactions. Here we proposed a new concept of dynamic protein–ligand int...
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Article
Open AccessStructure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets
The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical class...
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Chapter
Mode-of-Action-Guided, Molecular Modeling-Based Toxicity Prediction: A Novel Approach for In Silico Predictive Toxicology
is a sub-discipline of toxicology concerned with the development and use of computer-based models and methodology to understand and predict in a biological system (e.g., cells and organisms). Quantitative...
