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This is an introductory book on biochemical modeling available as of April 2nd, 2014. Page content: 390 pages, 169 Illustrations, 86 Exercises. Now at revision 1.13
Overview:
Computer models of biochemical systems are starting to play an increasingly important role in modern systems and synthetic biology. This monograph introduces students to some of the essential topics in biochemical modeling using differential equations and stochastic models. The book includes many hands-on modeling exercises and examples that illustrate many important concepts, including the stoichiometric networks, building models, running simulations, model fitting, stability of systems and multicompartment systems.
Errata for version 1.13:
Page 258: getEigenvalues should be getFullEigenValues
Page 125: rr.plot() should be r.plot()
Page 313: import matplotlib as plt should be import matplotlib.pyplot as plt
Page 313: plt.Axes.axes.set_xlabel should be plt.xlabel
Page 313: plt.Axes.axes.set_ylabel should be plt.ylabel
Pages 162, 270, 277, 284, 311, 312: All references to integrator=’cvode’ should be deleted
The above errata are fixed in version 1.14
Contents:
- Cellular Networks
- Kinetics in a Nutshell
- Stochiometric Networks
- Introduction to Modeling
- Differential Equation Models
- Stochastic Models
- How Systems Behave
- Multicompartment Models
- Fitting Models
- Parameter Estimation
- The Steady State
- Stability
- Modeling Feedforward Networks
- Behavior of Stochastic Models
Appendices:
Appendix A: List of Symbols and Abbreviations
Appendix B: Useful Numbers
Appendix C: Enzyme Kinetics in a Nutshell
Appendix D: Math Fundamentals
Appendix E: Statistics Reminder
Appendix F:Modeling Standards and Databases
Appendix G: Reference to Jarnac
Teaching Material
Free PowerPoint Slides (public domain):
