Kunal Roy

Chemometrics and Cheminformatics in Aquatic Toxicology (eBook, PDF)

• Format: PDF

Produktbeschreibung

CHEMOMETRICS AND CHEMINFORMATICS IN AQUATIC TOXICOLOGY Explore chemometric and cheminformatic techniques and tools in aquatic toxicology Chemometrics and Cheminformatics in Aquatic Toxicology delivers an exploration of the existing and emerging problems of contamination of the aquatic environment through various metal and organic pollutants, including industrial chemicals, pharmaceuticals, cosmetics, biocides, nanomaterials, pesticides, surfactants, dyes, and more. The book discusses different chemometric and cheminformatic tools for non-experts and their application to the analysis and modeling of toxicity data of chemicals to various aquatic organisms. You'll learn about a variety of aquatic toxicity databases and chemometric software tools and webservers as well as practical examples of model development, including illustrations. You'll also find case studies and literature reports to round out your understanding of the subject. Finally, you'll learn about tools and protocols including machine learning, data mining, and QSAR and ligand-based chemical design methods. Readers will also benefit from the inclusion of: * A thorough introduction to chemometric and cheminformatic tools and techniques, including machine learning and data mining * An exploration of aquatic toxicity databases, chemometric software tools, and webservers * Practical examples and case studies to highlight and illustrate the concepts contained within the book * A concise treatment of chemometric and cheminformatic tools and their application to the analysis and modeling of toxicity data Perfect for researchers and students in chemistry and the environmental and pharmaceutical sciences, Chemometrics and Cheminformatics in Aquatic Toxicology will also earn a place in the libraries of professionals in the chemical industry and regulators whose work involves chemometrics.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 592
• Erscheinungstermin: 1. Dezember 2021
• Englisch
• ISBN-13: 9781119681649
• Artikelnr.: 63119272

Autorenporträt

Kunal Roy, PhD, is Professor in the Department of Pharmaceutical Technology in Jadavpur University in Kolkata, India. He is a recipient of the Commonwealth Academic Staff Fellowship and the Marie Curie International Incoming Fellowship. His research focus is on the quantitative structure-activity relationship and chemometric modeling, with applications in drug design and ecotoxicological modeling.

Inhaltsangabe

Preface xxi

Part I Introduction 1

1 Water Quality and Contaminants of Emerging Concern (CECs) 3
Antonio Juan García-Fernández, Silvia Espín, Pilar Gómez-Ramírez, Pablo Sánchez-Virosta, and Isabel Navas

1.1 Introduction: Water Quality and Emerging Contaminants 3

1.2 Contaminants of Emerging Concern 6

1.3 Summary and Recommendations for Future Research 14

References 14

2 The Effects of Contaminants of Emerging Concern on Water Quality 23
Heiko L. Schoenfuss

2.1 Introduction 23

2.2 Assessing the Effects of CECs in Aquatic Life 27

2.3 Multiple Stressors 34

2.4 Conclusions 35

Acknowledgments 35

References 35

3 Chemometrics: Multivariate Statistical Analysis of Analytical Chemical and Biomolecular Data 45
Richard G. Brereton

3.1 Introduction 45

3.2 Historic Origins 45

3.3 Applied Statistics 46

3.4 Analytical and Physical Chemistry 48

3.5 Scientific Computing 49

3.6 Development from the 1980s 50

3.7 A Review of the Main Methods 52

3.8 Experimental Design 52

3.9 Principal Components Analysis and Pattern Recognition 53

3.10 Multivariate Signal Analysis 54

3.11 Multivariate Calibration 55

3.12 Digital Signal Processing and Time Series Analysis 56

3.13 Multiway Methods 56

3.14 Conclusion 56

References 57

4 An Introduction to Chemometrics and Cheminformatics 61
Chanin Nantasenamat

4.1 Brief History of Chemometrics/Cheminformatics 61

4.2 Current State of Cheminformatics 62

4.3 Common Cheminformatics Tasks 62

4.4 Cheminformatics Toolbox 63

4.5 Conclusion 65

References 65

Part II Chemometric and Cheminformatic Tools and Protocols 69

5 An Introduction to Some Basic Chemometric Tools 71
Lennart Eriksson, Erik Johansson, and Johan Trygg

5.1 Introduction 71

5.2 Example Datasets 72

5.3 Data Analytical Methods 73

5.4 Results 78

5.5 Discussion 85

References 87

6 From Data to Models: Mining Experimental Values with Machine Learning Tools 89
Giuseppina Gini and Emilio Benfenati

6.1 Introduction 89

6.2 Data and Models 91

6.3 Basic Methods in Model Development with ML 94

6.4 More Advanced ML Methodologies 103

6.5 Deep Learning 113

6.6 Conclusions 120

References 121

7 Machine Learning Approaches in Computational Toxicology Studies 125
Pravin Ambure, Stephen J. Barigye, and Rafael Gozalbes

7.1 Introduction 125

7.2 Toxicity Data Set Preparation 127

7.3 Machine-Learning Techniques 128

7.4 Model Evaluation 145

7.5 Freely Available Software Tools and Open-Source Libraries Relevant to Machine Learning 146

7.6 Concluding Remarks 148

Acknowledgment 148

References 148

8 Counter-Propagation Neural Networks for Modeling and Read Across in Aquatic (Fish) Toxicity 157
Viktor Drgan and Marjan Vra ko

8.1 Introduction 157

8.2 Examples of Counter-Propagation Artificial Neural Networks in Fish Toxicity Modeling 158

8.3 Counter-Propagation Artificial Neural Networks 163

8.4 Conclusions 164

References 164

9 Aiming High versus Aiming All: Aquatic Toxicology and QSAR Multitarget Models 167
Ana S. Moura and M. Natália D. S. Cordeiro

9.1 Introduction 167

9.2 Multitarget QSARS and Aquatic Toxicology 168

9.3 Biotargets and Aqueous Environmental As