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084 _aB280bGg Q1 TB
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245 0 _aHandbook of Statistical Systems Biology
260 _aWest Sessex :
_bJohn Wiley,
_c2011.
300 _axxi, 508p.
500 _aIncludes bibliographical references and Index 495-508p.
520 _aSystems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book:Provides a comprehensive account of inference techniques in systems biology.Introduces classical and Bayesian statistical methods for complex systems.Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems.Discusses various applications for statistical systems biology, such as gene regulation and signal transduction.Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies.Presents an in-depth presentation of reverse engineering approaches.Provides colour illustrations to explain key concepts.This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.
650 _aBiology.
650 _aStatistical systems biology.
_9815856
650 _aStatistics.
700 _aStumpf, Michael
_eeditor.
_9815857
700 _aBalding, David J.
_eeditor.
_9815858
700 _aGirolami, Mark
_eeditor.
_9472463
942 _hB280bGg Q1 TB
_cTEXL
_2CC
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999 _c16753
_d16753