Lutfun Nahar & Satyajit Dey Sarker 
Computational Phytochemistry [EPUB ebook] 

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Computational Phytochemistry, Second Edition, explores how recent advances in computational techniques and methods have been embraced by phytochemical researchers to enhance many of their operations, refocusing and expanding the possibilities of phytochemical studies. By applying computational aids and mathematical models to extraction, isolation, structure determination, and bioactivity testing, researchers can obtain highly detailed information about phytochemicals and optimize working approaches. This book aims to support and encourage researchers currently working with or looking to incorporate computational methods into their phytochemical work. Topics in this book include computational methods for predicting medicinal properties, optimizing extraction, isolating plant secondary metabolites, and building dereplicated phytochemical libraries. The roles of high-throughput screening, spectral data for structural prediction, plant metabolomics, and biosynthesis are all reviewed before the application of computational aids for assessing bioactivities and virtual screening is discussed. Illustrated with detailed figures and supported by practical examples, this book is an indispensable guide for all those involved with the identification, extraction, and application of active agents from natural products. This new edition captures remarkable advancements in mathematical modeling and computational methods that have been incorporated in phytochemical research, addressing, e.g., extraction, isolation, structure determination, and bioactivity testing of phytochemicals. – Includes step-by-step protocols for various computational and mathematical approaches applied to phytochemical research- Features clearly illustrated chapters contributed by highly reputable researchers- Covers all key areas in phytochemical research, including virtual screening and metabolomics

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语言 英语 ● 格式 EPUB ● ISBN 9780443161032 ● 编辑 Lutfun Nahar & Satyajit Dey Sarker ● 出版者 Elsevier Science ● 发布时间 2024 ● 下载 3 时 ● 货币 EUR ● ID 9372869 ● 复制保护 Adobe DRM
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