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Andrew R. Leach, V.J. Gillet An Introduction to Chemoinformatics


Книга "An Introduction to Chemoinformatics".

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Let Me Remember: The Poetry of Sara J. Leach is a charming volume of verse penned by a young woman inhabiting the bustling New York City of the 1930s. Sara J. Leach (1893-1970) received her impetus to put pen to paper and express her poetic musings while taking a correspondence course from the Poet Laureate of Florida, Vivian Laramore Rader. At the time, Sara shared a cozy apartment in New York with her husband, Lester Leach, who was a university professor. Sara had met Vivian during a visit to in-laws in the South, and Vivian was encouraging of Sara's literary leanings. Sara J. Leach gained her inspiration from the beautiful mayhem of Manhattan, the wonders of nature, the mystery of love and the comforts of family and friends.

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The primary application of cheminformatics is in the storage and search of information relating to chemical compounds. It uses techniques such as data mining, information storage etc. It uses techniques from many disciplines including computer science, mathematics, computational chemistry etc. to tackle these problems. This book aims at providing an introduction to this fascinating field. The book sets out the scope of chemoinformatics and deals with each scope area. The presentation is designed for those who are interested in knowing ‘What is Chemoinformatics?’. The book is aimed at final-year undergraduates students. It assumes no prior knowledge of the various disciplines except to some extent Chemistry and some basic mathematical concepts.

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An Introduction to Chemoinformatics, Andrew R. Leach, V.J ...

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Chemoinformatics draws upon techniques from many disciplines including computer science, mathematics, computational chemistry and data visualisation to tackle these problems.

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Chemoinformatics draws upon techniques from many disciplines including computer science, mathematics, computational chemistry and data visualisation to tackle these problems. This, the first text written specifically for this field, aims to provide an introduction to the major techniques of chemoinformatics. The first part of the book deals ...

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This book aims to provide an introduction to the major techniques of chemoinformatics. It is the first text written specifically for this field. The first part of the book deals with the representation of 2D and 3D molecular structures, the calculation of molecular descriptors and the construction of mathematical models.

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Andrew R. Leach, V.J. Gillet This book aims to provide an introduction to the major techniques of chemoinformatics. It is the first text written specifically for this field.

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Andrew R. Leach, V.J. Gillet This book aims to provide an introduction to the major techniques of chemoinformatics. It is the first text written specifically for this field.

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30 tutorials and more than 100 exercises in chemoinformatics, supported by online software and data sets Chemoinformatics is widely used in both academic and industrial chemical and biochemical research worldwide. Yet, until this unique guide, there were no books offering practical exercises in chemoinformatics methods. Tutorials in Chemoinformatics contains more than 100 exercises in 30 tutorials exploring key topics and methods in the field. It takes an applied approach to the subject with a strong emphasis on problem-solving and computational methodologies. Each tutorial is self-contained and contains exercises for students to work through using a variety of software packages. The majority of the tutorials are divided into three sections devoted to theoretical background, algorithm description and software applications, respectively, with the latter section providing step-by-step software instructions. Throughout, three types of software tools are used: in-house programs developed by the authors, open-source programs and commercial programs which are available for free or at a modest cost to academics. The in-house software and data sets are available on a dedicated companion website. Key topics and methods covered in Tutorials in Chemoinformatics include: Data curation and standardization Development and use of chemical databases Structure encoding by molecular descriptors, text strings and binary fingerprints The design of diverse and focused libraries Chemical data analysis and visualization Structure-property/activity modeling (QSAR/QSPR) Ensemble modeling approaches, including bagging, boosting, stacking and random subspaces 3D pharmacophores modeling and pharmacological profiling using shape analysis Protein-ligand docking Implementation of algorithms in a high-level programming language Tutorials in Chemoinformatics is an ideal supplementary text for advanced undergraduate and graduate courses in chemoinformatics, bioinformatics, computational chemistry, computational biology, medicinal chemistry and biochemistry. It is also a valuable working resource for medicinal chemists, academic researchers and industrial chemists looking to enhance their chemoinformatics skills.

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A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the books R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.

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