Handbook of Statistical Systems Biology - Tapa dura

Acerca del autor

Michael Stumpf, Theoretical Systems Biology at Imperial College London

David Balding, Statistical Genetics in the Institute of Genetics at University College London

Mark Girolami, Department of Computing Science and the Department of Statistics

De la contraportada

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 book:

• Provides a comprehensive account of inference techniques insystems biology.
• Introduces classical and Bayesian statistical methods forcomplex systems.
• Explores networks and graphical modeling as well as a widerange 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 engineeringapproaches.
• Provides colour illustrations to explain key concepts.

This handbook will be a key resource for researchers practisingsystems biology, and those requiring a comprehensive overview ofthis important field.