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This second eidtion explores new and updated techniques used to understand solid target-specific models in computational toxicology. Chapters are divided into four sections, detailing molecular descriptors, QSAR and read-across, molecular and data modeling techniques, computational toxicology in drug discovery, molecular fingerprints, AI techniques, and safe drug design. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge, Computational Toxicology: Methods and Protocols, Second Editon aims to ensure successful results in the further study of this vital field.
Dedication
Preface
Contributors
The Tools of the Game
QSAR: Using the Past to Study the Present
Molecular Similarity in Predictive Toxicology with a Focus on the q-RASAR Technique
Weight of Evidence: Criteria and Applications
Integration of QSAR and NAM in the Read-Across Process for an Effective and Relevant Toxicological Assessment
Molecular and Data Modeling
Automated Workflows for Data Curation and Machine Learning to Develop Quantitative Structure-Activity Relationships
Applicability Domain for Trustable Predictions
Approaching Pharmacological Space: Events and Components
The Potential of Molecular Docking for Predictive Toxicology
Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation
Applicative Examples of Predictive Toxicology
Toxicity Potential of Nutraceuticals
Development, Use, and Validation of (Q)SARs for Predicting Genotoxicity and Carcinogenicity: Experiences from Ital...
Adverse Outcome Pathways Mechanistically Describing Hepatotoxicity
Machine Learning in Early Prediction of Metabolism of Drugs
In Vitro Cell-Based MTT and Crystal Violet Assays for Drug Toxicity Screening
Recent Advances in Nanodrug Delivery Systems Production, Efficacy, Safety, and Toxicity
Investigating the Benefit-Risk Profile of Drugs: From Spontaneous Reporting Systems to Real-World Data for Pharmac...
MolPredictX: A Pioneer Mobile App Version for Online Biological Activity Predictions by Machine Learning Models
TIRESIA and TISBE: Explainable Artificial Intelligence Based Web Platforms for the Transparent Assessment of the D...
PFAS-Biomolecule Interactions: Case Study Using Asclepios Nodes and Automated Workflows in KNIME for Drug Discover...
Index