An Introduction to Systems Biology
Design Principles of Biological Circuits
1st Edition
Published on 1. July 2006
Book
Paperback/Softback
320 pages
978-1-58488-642-6 (ISBN)
Description
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Reviews / Votes
"[This text deserves] serious attention from any quantitative scientist or physicist who hopes to learn about modern biology. [It is] well written. ... Alon's book is the better place for physicists to start. It assumes no prior knowledge of or even interest in biology. Yet right from chapter 1, the author succeeds in explaining in an intellectually exciting way what the cell does and what degrees of freedom enable it to function. ... The book proceeds with detailed discussions of some of the key network motifs, circuit-element designs ... [and] focuses on concrete examples such as chemotaxis and developmental pattern formation. ... He draws the detailed strands together into an appealing and inspiring overview of biology. ... One final aspect that must be mentioned is the wonderful set of exercises that accompany each chapter. ... Alon's book should become a standard part of the training of graduate students in biological physics... ."-Nigel Goldenfeld, University of Illinois at Urbana-Champaign, Physics Today, June 2007
"...a superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He starts with a mathematical description of transcriptional activation and then describes some basic transcription-network motifs (patterns) that can be combined to form larger networks. ... Alon investigates networks at a higher level, including genomic regulatory networks. He does an excellent job of explaining and motivating a useful toolbox of engineering models and methods using network-based controls. ... will be a valuable and non-overlapping addition to a systems-biology curriculum."
-Eric Werner, Department of Physiology, Anatomy and Genetics, University of Oxford, Nature, Vol. 446, No. 29, March 2007
"I read Uri Alon's elegant book almost without stopping for breath. He perceives and explains so many simple regularities, so clearly, that the novice reading this book can move on immediately to research literature, armed with a grasp of the many connections between diverse phenomena."
-Philip Nelson, Professor of Physics, University of Pennsylvania, Philadelphia, USA
"... Beyond simply recounting recent results, Alon boldly articulates the basic principles underlying biological circuitry at different levels and shows how powerful they can be in understanding the complexity of living cells. For anyone who wants to understand how a living cell works, but thought they never would, this book is essential."
-Michael B. Elowitz, California Institute of Technology, Pasadena, USA
"Uri Alon offers a highly original perspective on systems biology, emphasizing the function of certain simple networks that appear as ubiquitous building blocks of living matter. The quest for simplicity - without losing contact with complex reality - is the only way to uncover the principles organizing biological systems. Alon writes with uncommon lucidity..."
-Boris Shraiman, University of California, Santa Barbara, USA
"This is a remarkable book that introduces not only a field but a way of thinking. Uri Alon describes in an elegant, simple way how principles such as stability, robustness and optimal design can be used to analyze and understand the evolution and behavior of living organisms. Alon's clear intuitive language and helpful examples offer - even to a mathematically naive reader - deep mathematical insights into biology. The community has been waiting for this book; it was worth the wait."
-Galit Lahav, Harvard Medical School, Boston, Massachusetts, USA
More details
Series
Language
English
Place of publication
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional and scholarly
Students, researchers, biologists, biophysicists, bio-engineers, bio-mathematicians and practitioners in bioinformatics, computational biology
Illustrations
4 pg color insert follows pg 112, 110 s/w Abbildungen, 8 s/w Tabellen, 4 s/w Photographien bzw. Rasterbilder
4 pg color insert follows pg 112; 4 Halftones, black and white; 8 Tables, black and white; 110 Illustrations, black and white
Dimensions
Height: 254 mm
Width: 178 mm
Weight
680 gr
ISBN-13
978-1-58488-642-6 (9781584886426)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
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08/2019
2nd Edition
Chapman & Hall/CRC
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07/2017
1st Edition
CRC Press
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Content
INTRODUCTION
TRANSCRIPTION NETWORKS, BASIC CONCEPTS
Introduction
The Cognitive Problem of the Cell
Elements of Transcription Networks
Dynamics and Response Time of Simple Gene Circuits
AUTO-REGULATION, A NETWORK MOTIF
Introduction
Patterns, Randomized Networks and Network Motifs
Autoregulation is a Network Motif
Negative Auto-Regulation Speeds the Response Time of Gene
Circuits
Negative Auto-Regulation Promotes Robustness to Fluctuations
in Production
Positive auto-regulation speeds responses and widens cell-cell variability
Summary
THE FEEDFORWARD LOOP NETWORK MOTIF
Introduction
The Number of Appearances of a Subgraph in Random
Networks
The Feedforward Loop (FFL) is a Network Motif
The Structure of the Feedforward Loop Circuit
Dynamics of the Coherent FFL with AND-Logic
The C1-FFL is a Sign-Sensitive Delay Element
The Incoherent FFL: a pulse generator and response accelerator
Why Are Some FFL Types Rare?
Convergent Evolution of FFLs
Summary
TEMPORAL PROGRAMS AND THE GLOBAL STRUCTURE OF TRANSCRIPTION NETWORKS
Introduction
The Single-Input Module (SIM) Network Motif
SIMs Can Generate Temporal Expression Programs
Topological Generalizations of Network Motifs
The Multi-Output FFL Can Generate FIFO Temporal Order
Signal Integration and Combinatorial Control: Bi-Fans and
Dense-Overlapping Regulons
Network Motifs and the Global Structure of Sensory
Transcription Networks
NETWORK MOTIFS IN DEVELOPMENTAL, SIGNAL-TRANSDUCTION AND NEURONAL NETWORKS
Introduction
Network Motifs in Developmental Transcription Networks:
Positive feedback loops and bistability
Motifs in Signal Transduction Networks
Information Processing Using Multi-Layer Perceptrons
Composite Network Motifs: Negative Feedback and Oscillator
Motifs
Network Motifs in the Neuronal Network of C. Elegans
Summary
ROBUSTNESS OF PROTEIN CIRCUITS, THE EXAMPLE OF BACTERIAL CHEMOTAXIS
The Robustness Principle
Bacterial Chemotaxis, or How Bacteria 'Think'
The Chemotaxis Protein Circuit of E. coli
Two Models Can Explain Exact Adaptation, One is Robust and
the Other Fine Tuned
The Barkai-Leibler model
Individuality and Robustness in Bacterial Chemotaxis
ROBUST PATTERNING IN DEVELOPMENT
Introduction to Morphogen Gradients
Exponential Gradients Are Not Robust
Increased Robustness by Self-Enhanced Morphogen
Degradation
Network Motifs That Provide Robust Patterning
The Robustness Principle Can Distinguish Between
Mechanisms of Fruit Fly Patterning
KINETIC PROOFREADING
Introduction
Kinetic Proofreading of the Genetic Code Can Reduce Error
Rates of Molecular Recognition
Recognition of Self and Non-Self by the Immune System
Kinetic Proofreading May Occur in Diverse Recognition
Processes in the Cell
OPTIMAL GENE CIRCUIT DESIGN
Introduction
Cost and Benefit Analysis of Gene circuits
Optimal Expression Level of a Protein Under Constant
Conditions
To Regulate or Not to Regulate: Optimal Regulation in Variable
Environments
Environmental Selection of the Feedforward Loop Network Motif
Summary
RULES FOR GENE REGULATION BASED ON ERROR MINIMIZATION
Introduction
The Savageau Demand Rules
Rules for Gene Regulation Based on Minimal Error Load
Demand Rules for Genes with Multiple Regulators
Summary
EPILOGUE: Simplicity in Biology
APPENDIX A: The Input-Function of a Gene, Michaelis-Menten and Hill Equations
APPENDIX B: Multi-Dimensional Input-Functions
APPENDIX C: Graph Properties of Transcription Networks
APPENDIX D: Cell-Cell Variability in Gene Expression
GLOSSARY
BIBLIOGRAPHY
TRANSCRIPTION NETWORKS, BASIC CONCEPTS
Introduction
The Cognitive Problem of the Cell
Elements of Transcription Networks
Dynamics and Response Time of Simple Gene Circuits
AUTO-REGULATION, A NETWORK MOTIF
Introduction
Patterns, Randomized Networks and Network Motifs
Autoregulation is a Network Motif
Negative Auto-Regulation Speeds the Response Time of Gene
Circuits
Negative Auto-Regulation Promotes Robustness to Fluctuations
in Production
Positive auto-regulation speeds responses and widens cell-cell variability
Summary
THE FEEDFORWARD LOOP NETWORK MOTIF
Introduction
The Number of Appearances of a Subgraph in Random
Networks
The Feedforward Loop (FFL) is a Network Motif
The Structure of the Feedforward Loop Circuit
Dynamics of the Coherent FFL with AND-Logic
The C1-FFL is a Sign-Sensitive Delay Element
The Incoherent FFL: a pulse generator and response accelerator
Why Are Some FFL Types Rare?
Convergent Evolution of FFLs
Summary
TEMPORAL PROGRAMS AND THE GLOBAL STRUCTURE OF TRANSCRIPTION NETWORKS
Introduction
The Single-Input Module (SIM) Network Motif
SIMs Can Generate Temporal Expression Programs
Topological Generalizations of Network Motifs
The Multi-Output FFL Can Generate FIFO Temporal Order
Signal Integration and Combinatorial Control: Bi-Fans and
Dense-Overlapping Regulons
Network Motifs and the Global Structure of Sensory
Transcription Networks
NETWORK MOTIFS IN DEVELOPMENTAL, SIGNAL-TRANSDUCTION AND NEURONAL NETWORKS
Introduction
Network Motifs in Developmental Transcription Networks:
Positive feedback loops and bistability
Motifs in Signal Transduction Networks
Information Processing Using Multi-Layer Perceptrons
Composite Network Motifs: Negative Feedback and Oscillator
Motifs
Network Motifs in the Neuronal Network of C. Elegans
Summary
ROBUSTNESS OF PROTEIN CIRCUITS, THE EXAMPLE OF BACTERIAL CHEMOTAXIS
The Robustness Principle
Bacterial Chemotaxis, or How Bacteria 'Think'
The Chemotaxis Protein Circuit of E. coli
Two Models Can Explain Exact Adaptation, One is Robust and
the Other Fine Tuned
The Barkai-Leibler model
Individuality and Robustness in Bacterial Chemotaxis
ROBUST PATTERNING IN DEVELOPMENT
Introduction to Morphogen Gradients
Exponential Gradients Are Not Robust
Increased Robustness by Self-Enhanced Morphogen
Degradation
Network Motifs That Provide Robust Patterning
The Robustness Principle Can Distinguish Between
Mechanisms of Fruit Fly Patterning
KINETIC PROOFREADING
Introduction
Kinetic Proofreading of the Genetic Code Can Reduce Error
Rates of Molecular Recognition
Recognition of Self and Non-Self by the Immune System
Kinetic Proofreading May Occur in Diverse Recognition
Processes in the Cell
OPTIMAL GENE CIRCUIT DESIGN
Introduction
Cost and Benefit Analysis of Gene circuits
Optimal Expression Level of a Protein Under Constant
Conditions
To Regulate or Not to Regulate: Optimal Regulation in Variable
Environments
Environmental Selection of the Feedforward Loop Network Motif
Summary
RULES FOR GENE REGULATION BASED ON ERROR MINIMIZATION
Introduction
The Savageau Demand Rules
Rules for Gene Regulation Based on Minimal Error Load
Demand Rules for Genes with Multiple Regulators
Summary
EPILOGUE: Simplicity in Biology
APPENDIX A: The Input-Function of a Gene, Michaelis-Menten and Hill Equations
APPENDIX B: Multi-Dimensional Input-Functions
APPENDIX C: Graph Properties of Transcription Networks
APPENDIX D: Cell-Cell Variability in Gene Expression
GLOSSARY
BIBLIOGRAPHY