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EBOOK
Author Nagarajan, Radhakrishnan.
Title Bayesian networks in R : with applications in systems biology / Radhakrishnan Nagarajan, Marco Scutari, Sophie Lebre.
Imprint New York, NY : Springer, 2013.

LOCATION CALL # STATUS MESSAGE
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LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Author Nagarajan, Radhakrishnan.
Series Use R! ; 48
Use R! ; 48.
Subject Bayesian statistical decision theory.
R (Computer program language)
Systems biology -- Statistical methods.
Alt Name Scutari, Marco.
Lèbre, Sophie.
Description 1 online resource.
polychrome rdacc
Contents Introduction -- Bayesian Networks in the Absence of Temporal Information -- Bayesian Networks in the Presence of Temporal Information -- Bayesian Network Inference Algorithms -- Parallel Computing for Bayesian Networks.
Bibliography Note Includes bibliographical references and index.
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.
ISBN 9781461464464 (electronic bk.)
1461464463 (electronic bk.)
1461464455
9781461464457
ISBN/ISSN 10.1007/978-1-4614-6446-4
OCLC # 842137782
Additional Format Print version: Druck-Ausgabe Nagarajan, Radhakrishnan. Bayesian Networks in R . With Applications in Systems Biology


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