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Full Description
Cheminformatic Modelling and Data Gap Filling for a Green and Sustainable Environment covers the theory and practices of chemical informatics, focusing on modelling various properties and endpoints related to chemicals for improved chemical management and the design of safer chemicals to promote environmental sustainability. Across four sections, this book outlines modelling techniques such as quantitative structure-property relationship (QSPR), read-across, and machine learning for modelling environmental endpoints of chemicals. OECD guidelines are discussed and considered for model development and validation, documentation using QSAR modelling reporting format (QMRF), and regulatory requirements for result presentation. This book offers full datasets, algorithm information and real-world case studies for all models and worked examples. This book will serve as an essential resource for chemists and environmental scientists working in green and sustainable chemistry, as well as students and academics at graduate level and above studying cheminformatics. This book will also be of interests for researchers working on developing new and sustainable chemicals and decision makers looking to make industrial processes more sustainable.
Contents
Section I: Introduction
1. Chemicals Strategy for a Sustainable Environment
2. Modern Modelling Approaches for Data Gap Filling
3. Aquatic Toxicology: Computational Approaches and Innovations
Section II: QSPR Modelling of Physicochemical Properties and Environmental Fate of Chemicals
4. QSPR Modelling of Physicochemical Properties of Environmentally Relevant Chemicals
5. OPERA QSPR Models for Environmentally Relevant Physicochemical Properties
6. Prediction of Hydrolysis and Biodegradation of Organophosphorus-Based Chemical Warfare Agents (Novichoks, G-series and V-series) Using In Silico Toxicology Methods
7. Machine Learning Models as Alternative Methods for Predicting Bioconcentration Factors
8. QSPR Modelling of Adsorption Capacity of Microplastics
9. Simulation of Physicochemical and Biochemical Behaviour of Nanoparticles Under Various Experimental Conditions
10. Modelling of Physicochemical Properties of Nanoparticles Using QSPR Analysis
11. Chemometric Modelling of Physicochemical Properties of Nanoparticles
Section III: Computational Modelling of Toxicity and Ecotoxicity of Chemicals
12. Computational Modelling of Acute Toxicity of Pharmaceuticals and Related Chemicals
13. Computational Modelling of Acute Toxicity of Nanoparticles
14. Computational Modelling of Acute and Chronic Toxicities of Organic Solvents
15. Computational Modelling of Acute and Chronic Toxicities of Chemicals of Emerging Concern
16. Computational Approaches in Toxicity Prediction: The Role of QSAR in Modern Chemical Risk Assessment for Water Ecosystems
17. Computational Modelling of Avian Toxicities: Risk Assessment of Chemicals
18. Computational Modelling of Genotoxicity and Carcinogenicity of Chemicals
19. Computational Modelling of Skin Sensitisation of Chemicals
20. Recent Advances in Modelling Chemical Mutagenicity and Carcinogenicity
21. Computational Modelling of Genotoxic Chemicals
Section IV: Additional Topics
22. Databases for Chemical Toxicity and Ecotoxicity
23. Open-Source Modelling Tools for Chemical Toxicity and Ecotoxicity
24. Chemical Language Models for Chemical Toxicity and Ecotoxicity Prediction
25. Application of AI/ML in Modelling Chemical Toxicity and Ecotoxicity
26. Multitask Learning and Transfer Learning Approaches in Target-Based Chemical Toxicity Modelling: GPCRs as an Example
27. In silico Modelling of Properties and Toxicities of Chemical Mixtures
28. Databases for Chemical and Physical Properties
29. Advanced Cheminformatics Models for Predicting PFAS Potency and Environmental Impact in Sustainable Chemistry, Powered by the Enalos Cloud Platform
30. Applying Partial Ordering Methodology to the Study of Environmental Pollutants
31. Cheminformatics in Life Cycle Assessment: Advancing Solvent, Toxicology and Chemical Synthesis for Sustainable Innovation
32. The VERA Tool: A Flexible Approach
33. MetaQSAR: A Comprehensive Tool for Automated QSAR Modelling
34. ProtoPRED, a Versatile, User-Friendly Platform for In Silico Predictions of Physicochemical, Eco(toxicological) and Pharmacokinetic Parameters in a Regulatory Context
