Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models, 1st Edition (Paperback) book cover

Fundamentals of Systems Biology

From Synthetic Circuits to Whole-cell Models, 1st Edition

By Markus W. Covert

CRC Press

367 pages | 120 B/W Illus.

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Description

For decades biology has focused on decoding cellular processes one gene at a time, but many of the most pressing biological questions, as well as diseases such as cancer and heart disease, are related to complex systems involving the interaction of hundreds, or even thousands, of gene products and other factors. How do we begin to understand this complexity?

Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models introduces students to methods they can use to tackle complex systems head-on, carefully walking them through studies that comprise the foundation and frontier of systems biology. The first section of the book focuses on bringing students quickly up to speed with a variety of modeling methods in the context of a synthetic biological circuit. This innovative approach builds intuition about the strengths and weaknesses of each method and becomes critical in the book’s second half, where much more complicated network models are addressed—including transcriptional, signaling, metabolic, and even integrated multi-network models.

The approach makes the work much more accessible to novices (undergraduates, medical students, and biologists new to mathematical modeling) while still having much to offer experienced modelers--whether their interests are microbes, organs, whole organisms, diseases, synthetic biology, or just about any field that investigates living systems.

Reviews

"Author has excellent command of both aspects of systems biology."

—Joel Bader, Johns Hopkins University, Baltimore, Maryland, USA

"… an excellent introduction to systems thinking and modeling in the context of complex biological problems. … uses concrete biological examples to develop systems concepts and model step by step, thus enabling the reader to understand the power of systems biology in the study of complex biological phenomena. … develops a deep intuition of systems thinking in the context of complex biological phenomena. This intuition is then translated into concrete systems modeling approaches enabling readers to apply the systems approach to their own problems."

—Prof Werner Dubitzky, University of Ulster

Table of Contents

BUILDING INTUITION

Variations on a Theme of Control

Learning Objectives

Variations

Autoregulation

Our Theme: A Typical Negative Autoregulatory Circuit

Summary

Recommended Reading

Variation: Boolean Representations

Learning Objectives

Boolean Logic and Rules

State Matrices

State Transitions

Dynamics

Timescales

Advantages and Disadvantages of Boolean Analysis

Summary

Recommended Reading

Problems

Variation: Analytical Solutions of Ordinary Differential Equations

Learning Objectives

Synthetic Biological Circuits

From Compartment Models to ODEs

Specifying and Simplifying ODEs with Assumptions

The Steady-State Assumption

Solving the System without Feedback: Removal of Activator

Key Properties of the System Dynamics

Solving the System without Feedback: Addition of Activator

Comparison of Modeling to Experimental Measurements

Addition of Autoregulatory Feedback

Comparison of the Regulated and Unregulated Systems

Summary

Recommended Reading

Problems

Variation: Graphical Analysis

Learning Objectives

Revisiting the Protein Synthesis ODEs

Plotting X versus dX/dt

Fixed Points and Vector Fields

From Vector Fields to Time-Course Plots

Nonlinearity

Bifurcation Analysis

Adding Feedback

Two-Equation Systems

Summary

Recommended Reading

Problems

Variation: Numerical Integration

Learning Objectives

The Euler Method

Accuracy and Error

The Midpoint Method

The Runge-Kutta Method

Summary

Recommended Reading

Problems

Variation: Stochastic Simulation

Learning Objectives

Single Cells and Low Molecule Numbers

Stochastic Simulations

The Probability that Two Molecules Interact and React in a Given Time Interval

The Probability of a Given Molecular Reaction Occurring over Time

The Relationship between Kinetic and Stochastic Constants

Gillespie's Stochastic Simulation Algorithm

Stochastic Simulation of Unregulated Gene Expression

Stochastic Simulations versus Other Modeling Approaches

Summary

Recommended Reading

Problems

FROM CIRCUITS TO NETWORKS

Transcriptional Regulation

Learning Objectives

Transcriptional Regulation and Complexity

More Complex Transcriptional Circuits

The Transcriptional Regulatory Feed-Forward Motif

Boolean Analysis of the Most Common Internally Consistent Feed-Forward Motif Identified in E. coli

An ODE-Based Approach to Analyzing the Coherent Feed-Forward Loop

Robustness of the Coherent Feed-Forward Loop

Experimental Interrogation of the Coherent Feed-Forward Loop

Changing the Interaction from an AND to an OR Relationship

The Single-Input Module

Just-in-Time Gene Expression

Generalization of the Feed-Forward Loop

An Example of a Multigene Feed-Forward Loop: Flagellar Biosynthesis in E. coli

Other Regulatory Motifs

Summary

Recommended Reading

Problems

Signal Transduction

Learning Objectives

Receptor-Ligand Binding to Form a Complex

Application to Real Receptor-Ligand Pairs

Formation of Larger Complexes

Protein Localization

The NF-kB Signaling Network

A Detailed Model of NF-kB Activity

Alternative Representations for the Same Process

Specifying Parameter Values from Data

Bounding Parameter Values

Model Sensitivity to Parameter Values

Reducing Complexity by Eliminating Parameters

Parameter Interactions

Summary

Recommended Reading

Problems

Metabolism

Learning Objectives

Cellular Metabolism

Metabolic Reactions

Compartment Models of Metabolite Concentration

The Michaelis-Menten Equation for Enzyme Kinetics

Determining Kinetic Parameters for the Michaelis-Menten System

Incorporating Enzyme Inhibitory Effects

Flux Balance Analysis

Steady-State Assumption and Exchange Fluxes

Solution Spaces

The Objective Function

Defining the Optimization Problem

Solving FBA Problems Using MATLAB

Applications of FBA to Large-Scale Metabolic Models

Using FBA for Metabolic Engineering

Summary

Recommended Reading

Problems

Integrated Models

Learning Objectives

Dynamic FBA: External versus Internal Concentrations

Environmental Constraints

Integration of FBA Simulations over Time

Comparing Dynamic FBA to Experimental Data

FBA and Transcriptional Regulation

Transcriptional Regulatory Constraints

Regulatory FBA: Method

REGULATORY FBA: Application

Toward Whole-Cell Modeling

Summary

Recommended Reading

Problems

Glossary

Subject Categories

BISAC Subject Codes/Headings:
SCI008000
SCIENCE / Life Sciences / Biology / General
SCI010000
SCIENCE / Biotechnology
SCI055000
SCIENCE / Physics
TEC007000
TECHNOLOGY & ENGINEERING / Electrical
TEC010000
TECHNOLOGY & ENGINEERING / Environmental / General