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Introduction to the Analysis of Biochemical and Genetic Systems

Eberhard O. Voit and Michael A. Savageau


Recent genome research has begun to produce unprecedented amounts of data that await analysis and interpretation. Clustering genes that are over- or under-expressed in response to a stimulus is an excellent strategy for identifying known and unknown genes involved in the response. However, clustering alone is not sufficient for explaining why the rates of some processes are increased whereas others are decreased, and why the degree of change may vary widely among processes. A true understanding of the well-orchestrated overall response with which an organism reacts to perturbations requires effective mathematical modeling approaches that integrate function on the genomic, biochemical, and physiological levels. These approaches must be sophisticated enough to capture with some validity the complexity observed in gene regulation and metabolism, but simple enough to be tractable when applied to phenomena of relevant magnitude.

This tutorial discusses Canonical Modeling, a biomathematical set of techniques that have proven very effective in the analysis of metabolic pathways and regulatory gene circuits. The tutorial consists of five modules. The introductory module discusses the need for mathematical models beyond simple kinetic rate laws and the concept of approximations. The second module introduces simple, effective rules for translating the diagram of a pathway or network into canonical model equations. The third module describes a typical model analysis, including assessments of steady states and explorations of dynamic features. The fourth module discusses methods of parameter estimation in the context of actual examples. In the final module, the attendee will have the opportunity to perform hands-on computer simulations of small systems in an interactive fashion, using the user-friendly freeware PLAS.


Module 1: Need for Models

Module 2: Maps and Equations;

Module 3: A Typical Analysis

Module 4: Parameter Estimation

Module 5: Computer Simulation with PLAS

General Discussion