Items related to Handbook of Statistical Systems Biology

Handbook of Statistical Systems Biology - Hardcover

Stumpf, Michael; Balding, David J.; Girolami, Mark

 
9780470710869: Handbook of Statistical Systems Biology
Hardcover
ISBN 10: 0470710861 ISBN 13: 9780470710869
Publisher: Wiley, 2011

Synopsis

Systems 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.

"synopsis" may belong to another edition of this title.

About the Author

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

From the Back Cover

Systems 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.

From the Inside Flap

Systems 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.

"About this title" may belong to another edition of this title.

Publisher
Wiley
Publication date
2011
Language
English
ISBN 10 
0470710861
ISBN 13 
9780470710869
Binding
Hardcover
Edition number
1
Number of pages
530