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A listing of forthcoming meetings, conventions, etc.
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.
Over the past few years, research in the field of quantitative structure-activity relationships (QSAR) in chemistry, biology, pharmacology, toxicology, and environmental sciences has seen strong growth. New journals and books have appeared in each of these fields, however, the combination of QSAR and environmental sciences is still in its infancy. After the success of the Workshop on Quantitative Structure-Activity Relationships (QSAR) in Environmental Toxicology, held at McMaster University, Aug ust 16-18, 1983, with the proceedings publ ished in 1984 [QSA R in Environmental Toxicology, Kaiser, K. L. E. (Ed. ), D. Reidel Pub!. Co. , Dordrecht, 406 p. , ISBN 90-277 -1776-1], it was time to hold another workshop in 1986. Indeed, the response by the scientific community was excellent with over 50 participants from Canada, Germany, Great Britain, Hungary, India, Japan, The Netherlands, United States, and Yugoslavia. Moreover, both breadth and depth of papers given were significantly improved and the workshop discussions were intense and frank. Regrettably, the number of participants, number of papers given and submitted for these proceedings made it impossible to include the workshop discussions of these papers. However, several manuscripts were revised on the basis of these discussions and, therefore, do reflect this very interactive workshop. This volume presents the majority of papers given at the 2nd International Workshop on QSAR in Environmental Toxicology, held at McMaster University, June 9-13, 1986. Many of these papers contain primary, new scientific data, equations and results which will not appear elsewhere.
First multi-year cumulation covers six years: 1965-70.
This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.
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.