In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. Methods involving the mapping and interpretation of Infra Red spectra and modelling environmental toxicology are included. This book is an excellent guide to this exciting field.

This book brings together drug design practitioners, all leaders in their field, who are actively advancing the field of quantitative methods to guide drug discovery, from structure-based design to empirical statistical models - from rule-based approaches to toxicology to the fields of bioinformatics and systems biology. The aim of the book is to show how various facets of the drug discovery process can be addressed in a quantitative fashion (ie: numerical analysis to enable robust predictions to be made). Each chapter includes a brief review of the topic showing the historical development of quantitative approaches, a survey/summary of the current state-of-the-art, a selection of well chosen examples with some worked through and an appreciation of what problems remain to be overcome as well as an indication of how the field may develop. After an overview of quantitative approaches to drug design the book describes the development of concepts of "drug-like properties", of quantitative structure-activity relationships and molecular modelling, and in particular, structure-based design approaches to guide lead optimisation. How to manage and describe chemical structures, underpins all quantitative approaches to drug design and these are described in the following chapters. The next chapter covers the value of a quantitative approach, and also the challenge which is to describe the confidence in any prediction, and methods to assess predictive model quality. The later chapters describe the application of quantitative approaches to describing and optimising potency, selectivity, drug metabolism and pharmacokinetic properties and toxicology, and the design of chemical libraries to feed the screening approaches to lead generation that underpin modern drug discovery. Finally the book describes the impact of bioinformatics, current status of predicting ligand affinity direct from the protein structure, and the application of quantitative approaches to predicting environmental risk. The book provides a summary of the current state-of-the-art in quantitative approaches to drug design, and future opportunities, but it also provides inspiration to drug design practitioners to apply careful design, to make best use of the quantitative methods that are available, while continuing to improve them. Drug discovery still relies heavily on random screening and empirical screening cascades to identify leads and drugs and the process has many failures to deliver only a small handful of drugs. With the rapidly escalating costs of drug discovery and development together with spiralling delivery, quantitative approaches hold the promise of shifting the balance of success, to enable drug discovery to maintain its economic viability.

Violence, forgiveness, and healing

Domestic violence is a widespread, though largely invisible, problem, often exacerbated by the pastoral urge to "keep the family together" at all costs. Yet if that is not a solution, how should the church relate to batterers?

"I believe that the Christian community, if it is to be genuinely a community of healing and hope, must attend to both the victims and the perpetrators of domestic violence", says David Livingston. Addressing the complex phenomenon of intimate violence against wives, lovers, and children, Livingston profiles batterers and battering and traces it to larger cultural pathologies. He explores the ambiguous role of religion and then offers practical advice of pastoral and programmatic efforts to embrace simultaneously the twin Christian imperatives of forgiveness and responsibility.

In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. Methods involving the mapping and interpretation of Infra Red spectra and modelling environmental toxicology are included. This book is an excellent guide to this exciting field.

Quantitative Structure-Activity Relationships (QSARs) are increasingly used to predict the harmful effects of chemicals to humans and the environment. The increased use of these methods in a variety of areas (academic, industrial, regulatory) results from a realization that very little toxicological or fate data is available on the vast amount of chemicals to which humans and the environment are exposed. Predicting Chemical Toxicity and Fate provides a comprehensive explanation of the state-of-the-art methods that are available to predict the effects of chemicals on humans and the environment. It describes the use of predictive methods to estimate the physiochemical properties, biological activities, and fate of chemicals. The methods described may be used to predict the properties of drugs before their development, and to predict the environmental effects of chemicals. These methods also reduce the cost of product development and the need for animal testing. This book fills an obvious need by providing a comprehensive explanation of these prediction methods. It is a practical book that illustrates the use of these techniques in real life scenarios. This book will demystify QSARs for those students unsure of them, and professionals in environmental toxicology and chemistry will find this a useful reference in their everyday working lives.