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Product Details 基本信息 ISBN-13 书号 9781071603222 Author 作者 Hanada Format 版本 精装 Pages Number 页数 252页 Publisher 出版社 Humana Press Publication Date 出版日期 2020-03-05 Language 语种 英语 Book Contents 内容简介 This volume explores the latest techniques used by researchers to study DNA electrophoresis, with focus on various species including bacteria, yeasts, and mammalian cells. The chapters in this book cover topics such as two-dimensional gel electrophoresis; DNA replication; pulsed-field gel electrophoresis; ChIP; and post-labeling/PAGE method for detection of DNA adducts. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.Cutting-edge and authoritati
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Product Details 基本信息 ISBN-13 书号 9789811927171 Author 作者 Masanori Hanada Format 版本 平装-胶订 Pages Number 页数 194页 Publisher 出版社 Springer Berlin Heidelberg Publication Date 出版日期 2023-10-21 Language 语种 其它(含多语) Book Contents 内容简介 This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves. The content consists of six
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预订 MCMC from Scratch: A Practical Introduction to Markov Cha 【全球购】进口原版图书,约5-8周到达国内后发出
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Product Details 基本信息 ISBN-13 书号 9789811927140 Author 作者 Hanada Format 版本 精装 Pages Number 页数 196页 Publisher 出版社 Springer Berlin Heidelberg Publication Date 出版日期 2022-07-28 Language 语种 其它(含多语) Book Contents 内容简介 This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves.The content consists of six chapters. Following Chapt
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