Handbook of Statistical Systems Biology
Systems Biology is now entering a mature phase in which the keyissues are characterising uncertainty and stochastic effects inmathematical models of biological systems. The area is movingtowards a full statistical analysis and probabilistic reasoningover the inferences that can be made from mathematical models. Thishandbook presents a comprehensive guide to the discipline forpractitioners and educators, in providing a full and detailedtreatment of these important and emerging subjects. Leading expertsin systems biology and statistics have come together to provideinsight in to the major ideas in the field, and in particularmethods of specifying and fitting models, and estimating theunknown parameters.
This handbook will be a key resource for researchers practisingsystems biology, and those requiring a comprehensive overview ofthis important field.
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Bayesian Inference and Computation
Data Integration Towards Understanding
Control Engineering Approaches toReverse Engineering Biomolecular Networks
Transcriptomic Technologies and Statistical Data
StatisticalData Analysis inMetabolomics 8 1 Introduction
Stochastic Dynamical Systems
Gaussian Process Inferencefor Differential Equation Models of Transcriptional Regulation
Model Identification by Utilizing Likelihood
1ODE Models forReaction Networks 20 2 Parameter Estimation
Introduction to Graphical Modelling
Recovering Genetic Network from Continuous
Advanced Applications of Bayesian Networks
3PPI network models 14 4Rangedependent graphs
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