03441nam 22007215 450 991043813600332120251116165604.09781461464464146146446310.1007/978-1-4614-6446-4(CKB)2560000000102854(EBL)1697681(OCoLC)842137782(SSID)ssj0000906270(PQKBManifestationID)11536121(PQKBTitleCode)TC0000906270(PQKBWorkID)10930518(PQKB)11386567(DE-He213)978-1-4614-6446-4(MiAaPQ)EBC1697681(PPN)169136213(EXLCZ)99256000000010285420130427d2013 u| 0engur|n|---|||||txtccrBayesian Networks in R with Applications in Systems Biology /by Radhakrishnan Nagarajan, Marco Scutari, Sophie Lèbre1st ed. 2013.New York, NY :Springer New York :Imprint: Springer,2013.1 online resource (168 p.)Use R!,2197-5744 ;48Description based upon print version of record.9781461464457 1461464455 Includes bibliographical references and index.Introduction -- Bayesian Networks in the Absence of Temporal Information -- Bayesian Networds in the Presence of Temporal Information -- Bayesian Network Inference Algorithms -- Parallel Computing for Bayesian Networks -- Solutions -- Index -- References.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.Use R!,2197-5744 ;48Mathematical statisticsData processingStatisticsCompilers (Computer programs)Statistics and ComputingStatistical Theory and MethodsCompilers and InterpretersMathematical statisticsData processing.Statistics.Compilers (Computer programs)Statistics and Computing.Statistical Theory and Methods.Compilers and Interpreters.519.542Nagarajan Radhakrishnan1063016Scutari Marco1757990Lèbre Sophie1757991MiAaPQMiAaPQMiAaPQBOOK9910438136003321Bayesian networks in R4196023UNINA