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.

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.

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
Phage lambda Decision Circuit Example
Spatial Gillespie
Reaction-Based Abstraction
Irrelevant Node Elimination
Enzymatic Approximations
Operator Site Reduction
Statistical Thermodynamical Model
Dimerization Reduction
Phage lambda 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.