Titlebook: Computational Toxicology; Methods and Protocol Orazio Nicolotti Book 2025Latest edition The Editor(s) (if applicable) and The Author(s), un

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书目名称Computational Toxicology影响因子(影响力)




书目名称Computational Toxicology影响因子(影响力)学科排名




书目名称Computational Toxicology网络公开度




书目名称Computational Toxicology网络公开度学科排名




书目名称Computational Toxicology被引频次




书目名称Computational Toxicology被引频次学科排名




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书目名称Computational Toxicology年度引用学科排名




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书目名称Computational Toxicology读者反馈学科排名

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Paul Doury,Yves Dirheimer,Serge Pattin so analyzed. QSAR is a mature technology and is part of a large body of in silico methods and other computational methods. The active debate about the acceptability of the QSAR models, about the way to communicate them, and the explanation to provide accompanies the development of today QSAR models

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Peter W. O’Hearn,Robert D. Tennentethods employed in Quantitative Structure-Activity Relationship (QSAR) studies. Lastly, the diverse applications of AD are addressed, underlining its widespread influence across different sectors. This chapter is intended to offer a thorough understanding of AD and its applications, particularly in

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The Varieties of Programming Languagemic parameters such as mean and range values..The reviewed examples emphasize that the pharmacological space can find fruitful applications in structure-based virtual screening as well as in toxicity prediction. In detail, in all reported examples, the inclusion of the pharmacological space paramete

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Design Space: The Final Frontier,g metabolism represents a powerful resource to be exploited during drug discovery and development. ML allows to improve in silico screening and safety assessments of drugs in advance, steering their path to marketing authorization. Prediction of biotransformation reactions and metabolites allows to

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Gilles Sicard,Estelle Labonne,Robin Rolland methods for their preparation (including the innovative microfluidic technique), mechanisms of interactions with biological systems, purification of nanoparticles, manufacture impurities, and nano-stability. This chapter places emphasis on the utilization of in silico, in vitro, and in vivo models

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https://doi.org/10.1007/978-90-481-9965-5rmacovigilance reporting systems in place at the global, European and in some European countries, and provide examples from recent literature of how the analysis of pharmacovigilance reports can provide evidence for unexpected and novel adverse drug reactions. Furthermore, we discuss the role of rea