Structure—Activity Relationships in Environmental Sciences
Structure—Activity Relationships in Environmental Sciences

Author: M. Nendza

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 279

ISBN-13: 1461558050

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Structure-Activity Relationships in Environmental Science is the first book of its kind that brings together information from a variety of sources into one document. It provides a comprehensive overview of the entire field of quantitative structure-activity relationships (QSARs) as well as being a reference for SAR experts. The book comprises three parts. Part One covers the theoretical background of structure-activity studies and Part Two deals with the practical applications of such methods in the environmental sciences. Part Three critically discusses SAR models with respect to their reliability and their aptness in environmental hazard and risk assessment. Recommendations are made as to which model to use and the case is presented for using QSARs in hazard assessment. The use of QSARs is becoming increasingly important since there is little experimental data available on environmentally relevant chemicals. Structure-Activity Relationships in Environmental Sciences will thus serve as an invaluable guide to both postgraduate and research scientists as well as professional ecologists.

Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment
Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment

Author: Roy, Kunal

Publisher: IGI Global

Published: 2015-02-28

Total Pages: 727

ISBN-13: 1466681373

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Quantitative structure-activity relationships (QSARs) represent predictive models derived from the application of statistical tools correlating biological activity or other properties of chemicals with descriptors representative of molecular structure and/or property. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment discusses recent advancements in the field of QSARs with special reference to their application in drug development, predictive toxicology, and chemical risk analysis. Focusing on emerging research in the field, this book is an ideal reference source for industry professionals, students, and academicians in the fields of medicinal chemistry and toxicology.

Issues in Environmental Research and Application: 2011 Edition
Issues in Environmental Research and Application: 2011 Edition

Author:

Publisher: ScholarlyEditions

Published: 2012-01-09

Total Pages: 3062

ISBN-13: 1464963630

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Issues in Environmental Research and Application: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Environmental Research and Application. The editors have built Issues in Environmental Research and Application: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Environmental Research and Application in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Environmental Research and Application: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment
Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment

Author: Kunal Roy

Publisher: Academic Press

Published: 2015-03-03

Total Pages: 494

ISBN-13: 0128016337

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Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR. Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment. Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods. - Includes numerous practical examples related to QSAR methods and applications - Follows the Organization for Economic Co-operation and Development principles for QSAR model development - Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools

3D QSAR in Drug Design
3D QSAR in Drug Design

Author: Hugo Kubinyi

Publisher: Springer Science & Business Media

Published: 1998-04-30

Total Pages: 413

ISBN-13: 0792347900

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Volumes 2 and 3 of the 3D QSAR in Drug Design series aim to review the progress being made in CoMFA and other 3D QSAR approaches since the publication of the highly successful first volume about four years ago. Volume 2 (Ligand-Protein Interactions and Molecular Similarity) divides into three sections dealing with Ligand-Protein Interactions, Quantum Chemical Models and Molecular Dynamics Simulations, and Pharmacophore Modelling and Molecular Similarity, respectively. Volume 3 (Recent Advances) is also divided into three sections, namely 3D QSAR Methodology: CoMFA and Related Approaches, Receptor Models and Other 3D QSAR Approaches, and 3D QSAR Applications. More than seventy distinguished scientists have contributed nearly forty reviews of their work and related research to these two volumes which are of outstanding quality and timeliness. These works present an up-to-date coverage of the latest developments in all fields of 3D QSAR.

Chemometrics and Cheminformatics in Aquatic Toxicology
Chemometrics and Cheminformatics in Aquatic Toxicology

Author: Kunal Roy

Publisher: John Wiley & Sons

Published: 2022-01-06

Total Pages: 596

ISBN-13: 1119681596

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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.

Advances in QSAR Modeling
Advances in QSAR Modeling

Author: Kunal Roy

Publisher: Springer

Published: 2017-05-22

Total Pages: 555

ISBN-13: 3319568507

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The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple disciplines such as chemistry, pharmacy, environmental and agricultural sciences addressing data gaps and modern regulatory requirements. Additionally, the applications of QSAR in food science and nanoscience have been included – two areas which have only recently been able to exploit this versatile tool. This timely addition to the series is aimed at graduate students, academics and industrial scientists interested in the latest advances and applications of QSAR.

Computational Molecular Modelling in Structural Biology
Computational Molecular Modelling in Structural Biology

Author:

Publisher: Academic Press

Published: 2018-08-24

Total Pages: 154

ISBN-13: 012813917X

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Computational Molecular modelling in Structural Biology, Volume 113, the latest release in the Advances in Protein Chemistry and Structural Biology, highlights new advances in the field, with this new volume presenting interesting chapters on charting the Bromodomain BRD4: Towards the Identification of Novel Inhibitors with Molecular Similarity and Receptor Mapping, and Computational Methods to Discover Compounds for the Treatment of Chagas Disease. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Advances in Protein Chemistry and Structural Biology series - Updated, with the latest information on Computational Molecular Modelling in Structural Biology

Predictive Analytics for Toxicology
Predictive Analytics for Toxicology

Author: Luis G. Valerio, Jr.

Publisher: CRC Press

Published: 2024-08-13

Total Pages: 253

ISBN-13: 1040101836

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Predictive data science is already in use in many fields, but its application in toxicology is new and sought after by non-animal alternative testing initiatives. Predictive Analytics for Toxicology: Applications in Discovery Science provides a comprehensive overview of the application of predictive analytics in the field of toxicology, highlighting its role and applications in discovery science. This book addresses the challenges of accurately predicting high-level endpoints of toxicity and explores the use of computational and artificial intelligence research to automate predictive toxicology. It underscores the importance of predictive toxicology in proposing and explaining adverse outcomes resulting from human exposures to specific toxicants, especially when experimental and observational data on the toxicant are incomplete or unavailable. Key features: Includes a plain language description of predictive analytics in toxicology adding an overview of the wide range of applications Examines the science of prediction, computational models as an automated science and comprehensive discussions on concepts of machine learning Opens the hood on AI and its applications in toxicology Features coverage on how in silico toxicity predictions are translational science tools The book integrates strategies and practices of predictive toxicology and offers practical information that students and professionals of the toxicology, chemical, and pharmaceutical industries will find essential. It fulfills the expectations of student researchers seeking to learn predictive analytics in toxicology. This book will energize scientists to conduct predictive toxicology modeling using artificial intelligence and machine learning, and inspire students and seasoned scientists interested in automated science to pick up new research using predictive in silico models to evaluate chemical-induced toxicity. With its focus on practical applications and real-world examples, this book serves as a guide for navigating the complex issues and practices of discovery toxicology. It is an essential resource for those interested in computer-based methods in toxicology, providing valuable insights into the use of predictive analytics.

Neural Networks in QSAR and Drug Design
Neural Networks in QSAR and Drug Design

Author: James Devillers

Publisher: Academic Press

Published: 1996-08-09

Total Pages: 309

ISBN-13: 0080537383

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Comprehensive and impeccably edited, Neural Networks in QSAR and Drug Design is the first book to present an all-inclusive coverage of the topic. The book provides a practice-oriented introduction to the different neural network paradigms, allowing the reader to easily understand and reproduce the results demonstrated. Numerous examples are detailed, demonstrating a variety of applications to QSAR and drug design.The contributors include some of the most distinguished names in the field, and the book provides an exhaustive bibliography, guiding readers to all the literature related to a particular type of application or neural network paradigm. The extensive index acts as a guide to the book, and makes retrieving information from chapters an easy task. A further research aid is a list of software with indications of availablility and price, as well as the editors scale rating the ease of use and interest/price ratio of each software package. The presentation of new, powerful tools for modeling molecular properties and the inclusion of many important neural network paradigms, coupled with extensive reference aids, makes Neural Networks in QSAR and Drug Design an essential reference source for those on the frontiers of this field. - Presents the first coverage of neural networks in QSAR and Drug Design - Allows easy understanding and reproduction of the results described within - Includes an exhaustive bibliography with more than 200 references - Provides a list of applicable software packages with availability and price