Handbook of Statistical Bioinformatics

Beschreibung

Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Introduces the state-of-arts techniques for statistical bioinformatics Focus on the interface between computational statistics and computational biology Covers key topics in modeling and analysis of massive data sets generated from high throughput biotechnology Includes supplementary material: sn.pub/extras

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Henry Horng-Shing Lu

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“This book puts together a nice collection of statistical methods covering a wide range of research topics in computational biology. … I can recommend the book as an overview on methods applied in computational biology for readers already experienced in basic computational statistics. Especially readers interested in systems biology topics will find a comprehensive summary of methods.” (Marc Zapatka, Biometrical Journal, Vol. 55 (4), 2013)

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