Bayesian networks in R : with applications in systems biology / Radhakrishnan Nagarajan, Marco Scutari, Sophie Lè̀bre.
Bayesian Networks in R with Applications in Systems Biology introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is gradually increased across the chapters wit...
Saved in:
Main Authors: | , , |
---|---|
Format: | Ebook |
Language: | English |
Published: |
New York :
Springer,
[2013]
|
Series: | Use R!.
|
Subjects: | |
Online Access: | Springer eBooks |
Summary: | Bayesian Networks in R with Applications in Systems Biology introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is gradually increased across the chapters with exercises and solutions for enhanced understanding and hands-on experimentation of key concepts. Applications focus on systems biology with emphasis on modeling pathways and signaling mechanisms from high throughput molecular data. Bayesian networks have proven to be especially useful abstractions in this regards as exemplified by their ability to discover new associations while validating known ones. It is also expected that the prevalence of publicly available high-throughput biological and healthcare data sets may encourage the audience to explore investigating novel paradigms using the approaches presented in the book. |
---|---|
Physical Description: | 1 online resource (xii, 157 pages) : illustrations. |
Format: | Mode of access: World Wide Web. |
Bibliography: | Includes bibliographical references and index. |
ISBN: | 1461464463 9781461464464 |