Engineering Genetic Circuits

An Introduction to Systems BioengineeringTakes a Clear and Systematic Engineering Approach to Systems Biology Focusing on genetic regulatory networks, Engineering Genetic Circuits presents the modeling, analysis, and design methods for systems biology. It discusses how to examine experimental data to learn about mathematical models, develop efficient abstraction and simulation methods to analyze these models, and use analytical methods to guide the design of new circuits. After reviewing the basic molecular biology and biochemistry principles needed to understand genetic circuits, the book describes modern experimental techniques and methods for discovering genetic circuit models from the data generated by experiments. The next four chapters present state-of-the-art methods for analyzing these genetic circuit models. The final chapter explores how researchers are beginning to use analytical methods to design synthetic genetic circuits. This text clearly shows how the success of systems biology depends on collaborations between engineers and biologists. From biomolecular observations to mathematical models to circuit design, it provides essential information on genetic circuits and engineering techniques that can be used to study biological systems.

An Engineer’s Guide to Genetic Circuits Chemical Reactions Macromolecules Genomes Cells and Their Structure Genetic Circuits Viruses Phage lambda: A Simple Genetic Circuit Learning Models Experimental Methods Experimental Data Cluster Analysis Learning Bayesian Networks Learning Causal Networks Experimental Design Differential Equation Analysis A Classical Chemical Kinetic Model Differential Equation Simulation Qualitative ODE Analysis Spatial Methods Stochastic Analysis A Stochastic Chemical Kinetic Model The Chemical Master Equation Gillespie’s Stochastic Simulation Algorithm Gibson/Bruck’s Next Reaction Method Tau-Leaping Relationship to Reaction Rate Equations Stochastic Petri-Nets Phagelambda Decision Circuit Example Spatial Gillespie Reaction-Based Abstraction Irrelevant Node Elimination Enzymatic Approximations Operator Site Reduction Statistical Thermodynamical Model Dimerization Reduction Phagelambda Decision Circuit Example Stoichiometry Amplification Logical Abstraction Logical Encoding Piecewise Models Stochastic Finite-State Machines Markov Chain Analysis Qualitative Logical Models Genetic Circuit Design Assembly of Genetic Circuits Combinational Logic Gates PoPS Gates Sequential Logic Circuits Future Challenges Solutions to Selected Problems References Glossary Index Sources and Problems appear at the end of each chapter.

Chris J. Myers is a professor in the Department of Electrical and Computer Engineering at the University of Utah. A co-inventor on four patents and author of more than 80 technical papers and the textbook Asynchronous Circuit Design, Dr. Myers received an NSF Fellowship in 1991 and an NSF CAREER award in 1996. His research interests include formal verification, asynchronous circuit design, and the analysis and design of genetic regulatory circuits.