{"product_id":"chemometrics-and-cheminformatics-in-aquatic-toxicology-isbn-9781119681595","title":"Chemometrics and Cheminformatics in Aquatic Toxicology","description":"\u003cb\u003eCHEMOMETRICS AND CHEMINFORMATICS IN AQUATIC TOXICOLOGY\u003c\/b\u003e \u003cp\u003e\u003cb\u003eExplore chemometric and cheminformatic techniques and tools in aquatic toxicology\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eChemometrics and Cheminformatics in Aquatic Toxicology\u003c\/i\u003e 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. \u003c\/p\u003e\u003cp\u003eYou’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. \u003c\/p\u003e\u003cp\u003eReaders will also benefit from the inclusion of: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA thorough introduction to chemometric and cheminformatic tools and techniques, including machine learning and data mining\u003c\/li\u003e \u003cli\u003eAn exploration of aquatic toxicity databases, chemometric software tools, and webservers\u003c\/li\u003e \u003cli\u003ePractical examples and case studies to highlight and illustrate the concepts contained within the book\u003c\/li\u003e \u003cli\u003eA concise treatment of chemometric and cheminformatic tools and their application to the analysis and modeling of toxicity data\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003ePerfect for researchers and students in chemistry and the environmental and pharmaceutical sciences, \u003ci\u003eChemometrics and Cheminformatics in Aquatic Toxicology\u003c\/i\u003e will also earn a place in the libraries of professionals in the chemical industry and regulators whose work involves chemometrics.Das Buch Chemometrics and Cheminformatics in Aquatic Toxicology befasst sich mit den bestehenden und neu auftretenden Problemen der Verschmutzung der aquatischen Umwelt durch verschiedene metallische und organische Schadstoffe, insbesondere Industriechemikalien, Pharmazeutika, Kosmetika, Biozide, Nanomaterialien, Pestizide, Tenside, Farbstoffe und viele weitere. Es werden verschiedene chemometrische und cheminformatische Instrumente für Laien beschrieben mitsamt ihrer Anwendung auf die Analyse und Modellierung der Toxizitätsdaten von Chemikalien in Bezug auf unterschiedliche aquatische Organismen.\u003cbr\u003e \u003cbr\u003e Eine Reihe von Datenbanken zur aquatischen Toxizität sowie chemometrische Softwaretools und Webserver werden vorgestellt und praktische Beispiele für die Modellentwicklung gegeben, einschließlich der entsprechenden Abbildungen. Darüber hinaus enthält das Werk Fallstudien und Literaturberichte, um das Verständnis des Themas abzurunden. Außerdem lernen die Leserinnen und Leser Werkzeuge und Protokolle wie maschinelles Lernen, Data Mining sowie Methoden des QSAR-basierten und ligandenbasierten chemischen Designs kennen.\u003cbr\u003e \u003cbr\u003e Darüber hinaus bietet das Werk:\u003cbr\u003e * Eine umfassende Einführung in chemometrische und cheminformatische Instrumente und Techniken, insbesondere maschinelles Lernen und Data Mining\u003cbr\u003e * Eine Darstellung von Datenbanken zur aquatischen Toxizität, chemometrischen Softwaretools und Webservern\u003cbr\u003e * Praktische Beispiele und Fallstudien zur Verdeutlichung und Veranschaulichung der im Buch enthaltenen Konzepte\u003cbr\u003e * Eine kompakte Erläuterung der chemometrischen und cheminformatischen Instrumente sowie ihrer Anwendung auf die Analyse und Modellierung von Toxizitätsdaten\u003cbr\u003e \u003cbr\u003e Chemometrics and Cheminformatics in Aquatic Toxicology ist ideal für Forschende und Studierende der Chemie sowie der Umwelt- und Pharmawissenschaften und sollte auch in den Bibliotheken von Fachleuten in der chemischen Industrie sowie Aufsichtsbehörden, die sich mit Chemometrie beschäftigen, einen Platz finden. \u003c\/p\u003e\u003cp\u003ePreface xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Water Quality and Contaminants of Emerging Concern (CECs) 3\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAntonio Juan García-Fernández, Silvia Espín, Pilar Gómez-Ramírez, Pablo Sánchez-Virosta, and Isabel Navas\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction: Water Quality and Emerging Contaminants 3\u003c\/p\u003e \u003cp\u003e1.2 Contaminants of Emerging Concern 6\u003c\/p\u003e \u003cp\u003e1.3 Summary and Recommendations for Future Research 14\u003c\/p\u003e \u003cp\u003eReferences 14\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 The Effects of Contaminants of Emerging Concern on Water Quality 23\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHeiko L. Schoenfuss\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 Assessing the Effects of CECs in Aquatic Life 27\u003c\/p\u003e \u003cp\u003e2.3 Multiple Stressors 34\u003c\/p\u003e \u003cp\u003e2.4 Conclusions 35\u003c\/p\u003e \u003cp\u003eAcknowledgments 35\u003c\/p\u003e \u003cp\u003eReferences 35\u003c\/p\u003e \u003cp\u003e3 \u003cb\u003eChemometrics: Multivariate Statistical Analysis of Analytical Chemical and Biomolecular Data 45\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRichard G. Brereton\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 45\u003c\/p\u003e \u003cp\u003e3.2 Historic Origins 45\u003c\/p\u003e \u003cp\u003e3.3 Applied Statistics 46\u003c\/p\u003e \u003cp\u003e3.4 Analytical and Physical Chemistry 48\u003c\/p\u003e \u003cp\u003e3.5 Scientific Computing 49\u003c\/p\u003e \u003cp\u003e3.6 Development from the 1980s 50\u003c\/p\u003e \u003cp\u003e3.7 A Review of the Main Methods 52\u003c\/p\u003e \u003cp\u003e3.8 Experimental Design 52\u003c\/p\u003e \u003cp\u003e3.9 Principal Components Analysis and Pattern Recognition 53\u003c\/p\u003e \u003cp\u003e3.10 Multivariate Signal Analysis 54\u003c\/p\u003e \u003cp\u003e3.11 Multivariate Calibration 55\u003c\/p\u003e \u003cp\u003e3.12 Digital Signal Processing and Time Series Analysis 56\u003c\/p\u003e \u003cp\u003e3.13 Multiway Methods 56\u003c\/p\u003e \u003cp\u003e3.14 Conclusion 56\u003c\/p\u003e \u003cp\u003eReferences 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 An Introduction to Chemometrics and Cheminformatics 61\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eChanin Nantasenamat\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Brief History of Chemometrics\/Cheminformatics 61\u003c\/p\u003e \u003cp\u003e4.2 Current State of Cheminformatics 62\u003c\/p\u003e \u003cp\u003e4.3 Common Cheminformatics Tasks 62\u003c\/p\u003e \u003cp\u003e4.4 Cheminformatics Toolbox 63\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 65\u003c\/p\u003e \u003cp\u003eReferences 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Chemometric and Cheminformatic Tools and Protocols 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 An Introduction to Some Basic Chemometric Tools 71\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eLennart Eriksson, Erik Johansson, and Johan Trygg\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 71\u003c\/p\u003e \u003cp\u003e5.2 Example Datasets 72\u003c\/p\u003e \u003cp\u003e5.3 Data Analytical Methods 73\u003c\/p\u003e \u003cp\u003e5.4 Results 78\u003c\/p\u003e \u003cp\u003e5.5 Discussion 85\u003c\/p\u003e \u003cp\u003eReferences 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 From Data to Models: Mining Experimental Values with Machine Learning Tools 89\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGiuseppina Gini and Emilio Benfenati\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 89\u003c\/p\u003e \u003cp\u003e6.2 Data and Models 91\u003c\/p\u003e \u003cp\u003e6.3 Basic Methods in Model Development with ML 94\u003c\/p\u003e \u003cp\u003e6.4 More Advanced ML Methodologies 103\u003c\/p\u003e \u003cp\u003e6.5 Deep Learning 113\u003c\/p\u003e \u003cp\u003e6.6 Conclusions 120\u003c\/p\u003e \u003cp\u003eReferences 121\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Machine Learning Approaches in Computational Toxicology Studies 125\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePravin Ambure, Stephen J. Barigye, and Rafael Gozalbes\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 125\u003c\/p\u003e \u003cp\u003e7.2 Toxicity Data Set Preparation 127\u003c\/p\u003e \u003cp\u003e7.3 Machine-Learning Techniques 128\u003c\/p\u003e \u003cp\u003e7.4 Model Evaluation 145\u003c\/p\u003e \u003cp\u003e7.5 Freely Available Software Tools and Open-Source Libraries Relevant to Machine Learning 146\u003c\/p\u003e \u003cp\u003e7.6 Concluding Remarks 148\u003c\/p\u003e \u003cp\u003eAcknowledgment 148\u003c\/p\u003e \u003cp\u003eReferences 148\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Counter-Propagation Neural Networks for Modeling and Read Across in Aquatic (Fish) Toxicity 157\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eViktor Drgan and Marjan Vračko\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 157\u003c\/p\u003e \u003cp\u003e8.2 Examples of Counter-Propagation Artificial Neural Networks in Fish Toxicity Modeling 158\u003c\/p\u003e \u003cp\u003e8.3 Counter-Propagation Artificial Neural Networks 163\u003c\/p\u003e \u003cp\u003e8.4 Conclusions 164\u003c\/p\u003e \u003cp\u003eReferences 164\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Aiming High versus Aiming All: Aquatic Toxicology and QSAR Multitarget Models 167\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAna S. Moura and M. Natália D. S. Cordeiro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 167\u003c\/p\u003e \u003cp\u003e9.2 Multitarget QSARS and Aquatic Toxicology 168\u003c\/p\u003e \u003cp\u003e9.3 Biotargets and Aqueous Environmental Assessment: Solutions and Recommendations 175\u003c\/p\u003e \u003cp\u003e9.4 Future Perspectives and Conclusion 175\u003c\/p\u003e \u003cp\u003eReferences 176\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Chemometric Approaches to Evaluate Interspecies Relationships and Extrapolation in Aquatic Toxicity 181\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eS. Raimondo, C.M. Lavelle, and M.G. Barron\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 181\u003c\/p\u003e \u003cp\u003e10.2 Acute Toxicity Estimation 183\u003c\/p\u003e \u003cp\u003e10.3 Sublethal Toxicity Extrapolation 186\u003c\/p\u003e \u003cp\u003e10.4 Discussion 191\u003c\/p\u003e \u003cp\u003e10.5 Conclusions 192\u003c\/p\u003e \u003cp\u003eDisclaimer 192\u003c\/p\u003e \u003cp\u003eReferences 193\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Case Studies and Literature Reports 201\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 The QSAR Paradigm to Explore and Predict Aquatic Toxicity 203\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFotios Tsopelas and Anna Tsantili-Kakoulidou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 203\u003c\/p\u003e \u003cp\u003e11.2 Application of QSAR Methodology to Predict Aquatic Toxicity 204\u003c\/p\u003e \u003cp\u003e11.3 QSAR for Narcosis – The Impact of Hydrophobicity 209\u003c\/p\u003e \u003cp\u003e11.4 Excess Toxicity – Overview 213\u003c\/p\u003e \u003cp\u003e11.5 Predictions of Bioconcentration Factor 216\u003c\/p\u003e \u003cp\u003e11.6 Conclusions 218\u003c\/p\u003e \u003cp\u003eReferences 219\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Application of Cheminformatics to Model Fish Toxicity 227\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSorin Avram, Simona Funar-Timofei, and Gheorghe Ilia\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 227\u003c\/p\u003e \u003cp\u003e12.2 Fish Toxicities 228\u003c\/p\u003e \u003cp\u003e12.3 Toxicity in Fish Families and Species 229\u003c\/p\u003e \u003cp\u003e12.4 The Fathead Minnow, the Rainbow Trout, and the Bluegill 231\u003c\/p\u003e \u003cp\u003e12.5 Toxicity Variations in FIT Compounds 232\u003c\/p\u003e \u003cp\u003e12.6 Modeling Wide-Range Toxicity Compounds 233\u003c\/p\u003e \u003cp\u003e12.7 Further Evaluations 236\u003c\/p\u003e \u003cp\u003e12.8 Alternative Approaches 237\u003c\/p\u003e \u003cp\u003e12.9 Mechanisms of Action 238\u003c\/p\u003e \u003cp\u003e12.10 Conclusions 239\u003c\/p\u003e \u003cp\u003eAcknowledgments 239\u003c\/p\u003e \u003cp\u003eAbbreviations List 239\u003c\/p\u003e \u003cp\u003eReferences 240\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Chemometric Modeling of Algal and Daphnia Toxicity 243\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eLuminita Crisan, Ana Borota, Alina Bora, Simona Funar-Timofei, and Gheorghe Ilia\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 243\u003c\/p\u003e \u003cp\u003e13.2 Algae Class 247\u003c\/p\u003e \u003cp\u003e13.3 Daphniidae Family 256\u003c\/p\u003e \u003cp\u003e13.4 Interspecies Correlation Estimation for Algal and Daphnia Aquatic Toxicity 262\u003c\/p\u003e \u003cp\u003e13.5 Conclusions 267\u003c\/p\u003e \u003cp\u003eAbbreviations List 268\u003c\/p\u003e \u003cp\u003eReferences 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Chemometric Modeling of Algal Toxicity 275\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMelek Türker Saçan, Serli Önlü, and Gulcin Tugcu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 275\u003c\/p\u003e \u003cp\u003e14.2 Criteria Set for the Comparison of Selected QSAR Models 277\u003c\/p\u003e \u003cp\u003e14.3 Literature MLR Studies on Algae 283\u003c\/p\u003e \u003cp\u003e14.4 Conclusion 288\u003c\/p\u003e \u003cp\u003eReferences 289\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Chemometric Modeling of Daphnia Toxicity 293\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAmit Kumar Halder and Maria Natália Dias Soeiro Cordeiro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 293\u003c\/p\u003e \u003cp\u003e15.2 QSTR and QSTTR Analyses 294\u003c\/p\u003e \u003cp\u003e15.3 QSTR\/QSTT\/QSTTR Modeling of Daphnia Toxicity 295\u003c\/p\u003e \u003cp\u003e15.4 Mechanistic Interpretations of Chemometric Models 309\u003c\/p\u003e \u003cp\u003e15.5 Conclusive Remarks and Future Directions 310\u003c\/p\u003e \u003cp\u003eAcknowledgment 311\u003c\/p\u003e \u003cp\u003eReferences 311\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Chemometric Modeling of Daphnia Toxicity: Quantum-Mechanical Insights 319\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eReenu and Vikas\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 319\u003c\/p\u003e \u003cp\u003e16.2 Quantum-Mechanical Methods 321\u003c\/p\u003e \u003cp\u003e16.3 Quantum-Mechanical Descriptors for Daphnia Toxicity 323\u003c\/p\u003e \u003cp\u003e16.4 Concluding Remarks and Future Outlook 325\u003c\/p\u003e \u003cp\u003eReferences 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Chemometric Modeling of Toxicity of Chemicals to Tadpoles 331\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKabiruddin Khan and Kunal Roy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 331\u003c\/p\u003e \u003cp\u003e17.2 Overview and Morphology of Tadpoles 332\u003c\/p\u003e \u003cp\u003e17.3 Reports of Tadpole Toxicity Due Various Environmental Contaminants: What Do We Know So Far? 340\u003c\/p\u003e \u003cp\u003e17.4 In silico Models Reported for Tadpole Ecotoxicity: A Literature Review 341\u003c\/p\u003e \u003cp\u003e17.5 Application of QSARs or Related Approaches in Modeling Tadpole Toxicity: A Future Perspective 351\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 351\u003c\/p\u003e \u003cp\u003eAcknowledgment 351\u003c\/p\u003e \u003cp\u003eReferences 352\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Chemometric Modeling of Toxicity of Chemicals to Marine Bacteria 359\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKabiruddin Khan and Kunal Roy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 359\u003c\/p\u003e \u003cp\u003e18.2 Marine Bacteria and Their Role in Nitrogen Fixing 360\u003c\/p\u003e \u003cp\u003e18.3 Marine Bacteria as Biomarkers for Ecotoxicity Estimation 362\u003c\/p\u003e \u003cp\u003e18.4 Chemometric Tools Applied in Ecotoxicity Evaluation of Marine Bacteria 363\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 373\u003c\/p\u003e \u003cp\u003eAcknowledgment 373\u003c\/p\u003e \u003cp\u003eReferences 374\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Chemometric Modeling of Pesticide Aquatic Toxicity 377\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAlina Bora and Simona Funar-Timofei\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 377\u003c\/p\u003e \u003cp\u003e19.2 QSARs Models 380\u003c\/p\u003e \u003cp\u003e19.3 Conclusions 386\u003c\/p\u003e \u003cp\u003eAbbreviations List 386\u003c\/p\u003e \u003cp\u003eReferences 387\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Contribution of Chemometric Modeling to Chemical Risks Assessment for Aquatic Plants: State-of-the-Art 391\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMabrouk Hamadache, Abdeltif Amrane, Othmane Benkortbi, and Salah Hanini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 391\u003c\/p\u003e \u003cp\u003e20.2 Definition and Classification 391\u003c\/p\u003e \u003cp\u003e20.3 Advantage of Aquatic Plants 392\u003c\/p\u003e \u003cp\u003e20.4 Contaminants and Their Toxicity 394\u003c\/p\u003e \u003cp\u003e20.5 Chemometrics for Aquatic Plants Toxicity 400\u003c\/p\u003e \u003cp\u003e20.6 Review of Literature on Chemometrics for Aquatic Plants Toxicity 400\u003c\/p\u003e \u003cp\u003e20.7 Conclusions 406\u003c\/p\u003e \u003cp\u003eReferences 407\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Application of 3D-QSAR Approaches to Classification and Prediction of Aquatic Toxicity 417\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSehan Lee and Mace G. Barron\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 417\u003c\/p\u003e \u003cp\u003e21.2 Principles of CAPLI 3D-QSAR 419\u003c\/p\u003e \u003cp\u003e21.3 Applications in Chemical Classification and Toxicity Prediction 426\u003c\/p\u003e \u003cp\u003e21.4 Limitation and Potential Improvement 429\u003c\/p\u003e \u003cp\u003e21.5 Conclusions and Recommendations 430\u003c\/p\u003e \u003cp\u003eAcknowledgments 430\u003c\/p\u003e \u003cp\u003eReferences 430\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 QSAR Modeling of Aquatic Toxicity of Cationic Polymers 433\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHans Sanderson, Pathan M. Khan, Supratik Kar, Kunal Roy, Anna M.B. Hansen, Kristin Connors, and Scott Belanger\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 433\u003c\/p\u003e \u003cp\u003e22.2 Materials and Methods 434\u003c\/p\u003e \u003cp\u003e22.3 Results and Discussion 440\u003c\/p\u003e \u003cp\u003e22.4 Conclusions 450\u003c\/p\u003e \u003cp\u003eAcknowledgments 450\u003c\/p\u003e \u003cp\u003eReferences 451\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Tools and Databases 453\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 In Silico Platforms for Predictive Ecotoxicology: From Machine Learning to Deep Learning 455\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eYong Oh Lee and Baeckkyoung Sung\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 455\u003c\/p\u003e \u003cp\u003e23.2 Machine Learning and Deep Learning 456\u003c\/p\u003e \u003cp\u003e23.3 Toxicity Prediction Modeling 458\u003c\/p\u003e \u003cp\u003e23.4 Challenges and Future Directions 463\u003c\/p\u003e \u003cp\u003eReferences 464\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 The Use and Evolution of Web Tools for Aquatic Toxicology Studies 473\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRenata P. B. Menezes, Natália F. Sousa, Luana de Morais e Silva, Luciana Scotti, Wilton Silva Lopes, and Marcus T. Scotti\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24.1 Introduction 473\u003c\/p\u003e \u003cp\u003e24.2 Methodologies Used in Aquatic Toxicology Tests 474\u003c\/p\u003e \u003cp\u003e24.3 Web Tools Used in Aquatic Toxicology 482\u003c\/p\u003e \u003cp\u003e24.4 Perspectives 487\u003c\/p\u003e \u003cp\u003eReferences 488\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 The Tools for Aquatic Toxicology within the VEGAHUB System 493\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eEmilio Benfenati, Anna Lombardo, Viktor Drgan, Marjana Novič, and Alberto Manganaro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25.1 Introduction 493\u003c\/p\u003e \u003cp\u003e25.2 The VEGA Models 495\u003c\/p\u003e \u003cp\u003e25.3 ToxRead and Read-Across Within VEGAHUB 505\u003c\/p\u003e \u003cp\u003e25.4 Prometheus and JANUS 506\u003c\/p\u003e \u003cp\u003e25.5 The Future Developments 508\u003c\/p\u003e \u003cp\u003e25.6 Conclusions 509\u003c\/p\u003e \u003cp\u003eReferences 510\u003c\/p\u003e \u003cp\u003e\u003cb\u003e26 Aquatic Toxicology Databases 513\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSupratik Kar and Jerzy Leszczynski\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e26.1 Introduction 513\u003c\/p\u003e \u003cp\u003e26.2 Aquatic Toxicity 514\u003c\/p\u003e \u003cp\u003e26.3 Importance of Aquatic Toxicity Databases 516\u003c\/p\u003e \u003cp\u003e26.4 Characteristic of an Ideal Aquatic Toxicity Database 516\u003c\/p\u003e \u003cp\u003e26.5 Aquatic Toxicology Databases 516\u003c\/p\u003e \u003cp\u003e26.6 Overview and Conclusion 524\u003c\/p\u003e \u003cp\u003eAcknowledgments 524\u003c\/p\u003e \u003cp\u003eConflicts of Interest 525\u003c\/p\u003e \u003cp\u003eReferences 525\u003c\/p\u003e \u003cp\u003e\u003cb\u003e27 Computational Tools for the Assessment and Substitution of Biocidal Active Substances of Ecotoxicological Concern: The LIFE-COMBASE Project 527\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMaría Blázquez, Oscar Andreu-Sánchez, Arantxa Ballesteros, María Luisa Fernández-Cruz, Carlos Fito, Sergi Gómez-Ganau, Rafael Gozalbes, David Hernández-Moreno, Jesus Vicente de Julián-Ortiz, Anna Lombardo, Marco Marzo, Irati Ranero, Nuria Ruiz-Costa, Jose Vicente Tarazona-Díez, and Emilio Benfenati\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e27.1 Introduction 527\u003c\/p\u003e \u003cp\u003e27.2 Database Compilation 530\u003c\/p\u003e \u003cp\u003e27.3 Development of the QSAR Models 531\u003c\/p\u003e \u003cp\u003e27.4 Prediction of Metabolites and their Associated Toxicity 533\u003c\/p\u003e \u003cp\u003e27.5 Implementation of the In Silico QSARs Within VEGA and Integration with Read Across Models in ToxRead 534\u003c\/p\u003e \u003cp\u003e27.6 Implementation of the LIFE-COMBASE Decision Support System 537\u003c\/p\u003e \u003cp\u003e27.7 Implementation of the LIFE-COMBASE Mobile App 543\u003c\/p\u003e \u003cp\u003e27.8 Concluding Remarks 543\u003c\/p\u003e \u003cp\u003eAcknowledgments 544\u003c\/p\u003e \u003cp\u003eReferences 544\u003c\/p\u003e \u003cp\u003e\u003cb\u003e28 Image Analysis and Deep Learning Web Services for Nano informatics 547\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAnastasios G. Papadiamantis, Antreas Afantitis, Andreas Tsoumanis, Pantelis Karatzas, Philip Doganis, Dimitra-Danai Varsou, Haralambos Sarimveis, Laura-Jayne A. Ellis, Eugenia Valsami-Jones, Iseult Lynch, and Georgia Melagraki\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e27.1 Introduction 547\u003c\/p\u003e \u003cp\u003e27.2 NanoXtract 549\u003c\/p\u003e \u003cp\u003e27.3 DeepDaph 556\u003c\/p\u003e \u003cp\u003e27.4 Conclusions 560\u003c\/p\u003e \u003cp\u003eAcknowledgments 561\u003c\/p\u003e \u003cp\u003eReferences 561\u003c\/p\u003e \u003cp\u003eIndex 565\u003c\/p\u003e \u003cp\u003e\u003cb\u003eKunal Roy, PhD, \u003c\/b\u003eis 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.\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eExplore chemometric and cheminformatic techniques and tools in aquatic toxicology\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eChemometrics and Cheminformatics in Aquatic Toxicology\u003c\/i\u003e 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. \u003c\/p\u003e\u003cp\u003eYou’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. \u003c\/p\u003e\u003cp\u003eReaders will also benefit from the inclusion of: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA thorough introduction to chemometric and cheminformatic tools and techniques, including machine learning and data mining\u003c\/li\u003e \u003cli\u003eAn exploration of aquatic toxicity databases, chemometric software tools, and webservers\u003c\/li\u003e \u003cli\u003ePractical examples and case studies to highlight and illustrate the concepts contained within the book\u003c\/li\u003e \u003cli\u003eA concise treatment of chemometric and cheminformatic tools and their application to the analysis and modeling of toxicity data\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003ePerfect for researchers and students in chemistry and the environmental and pharmaceutical sciences, \u003ci\u003eChemometrics and Cheminformatics in Aquatic Toxicology\u003c\/i\u003e will also earn a place in the libraries of professionals in the chemical industry and regulators whose work involves chemometrics.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988910227685,"sku":"NP9781119681595","price":242.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119681595.jpg?v=1761782016","url":"https:\/\/k12savings.com\/products\/chemometrics-and-cheminformatics-in-aquatic-toxicology-isbn-9781119681595","provider":"K12savings","version":"1.0","type":"link"}