| 期刊全稱 | A Primer on QSAR/QSPR Modeling | | 期刊簡稱 | Fundamental Concepts | | 影響因子2023 | Kunal Roy,Supratik Kar,Rudra Narayan Das | | 視頻video | http://file.papertrans.cn/142/141923/141923.mp4 | | 發(fā)行地址 | A brief introduction for the quick understanding of QSAR/QSPR modeling concepts.No previous knowledge in the field is needed.Suitable illustrations are provided for quick understanding.At present, no | | 學(xué)科分類 | SpringerBriefs in Molecular Science | | 圖書封面 |  | | 影響因子 | .This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy. With this in mind, the authors have carefully compiled this brief in order to provide a thorough and painless introduction to the fundamental concepts of QSAR/QSPR model | | Pindex | Book 2015 |
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