As the 21st century approaches, there is little doubt that the tools and resources are available to unlock all the secrets of Quantitative Structure-Activity Relationships (QSAR) in order to design more efficient drugs and safer chemicals. The comparison QSAR models provide are a key to reach a deep understanding of the foundation and a better optimisation of the use of these statistical tools. Seeking out the similarities and differences among QSAR Models allows the user to estimate their simulation performances, find chemo-taxonomical links, and uncover In vivo/In Vitro relationships. The purpose of this book is to highlight the multifaceted aspect of the term "comparative QSAR" by bringing together QSAR experts of various origins and allowing them to offer their views on this diverse subject.
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James Devillers, Centre de Traitement de l'Information Scientifique, France
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