- 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.
Keywords: Statistical Genetics / Microarray Analysis, Bayesian methodology, Bayesian methodology systems biology, Dynamical systems biology, Statistical models, 3D visualisations biology, proteomic technologies statistics, pharmacodynamics statistics