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Introduction to Systems Biology:

And the Design Principles of Biological Networks
Front Cover
8 Reviews
CRC Press, 2007 - Mathematics - 301 pages
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.

  

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Review: An Introduction to Systems Biology: Design Principles of Biological Circuits

User Review  - Paul - Goodreads

This book represents one of the first comprehensive treatments of systems biology in the form of a textbook intended for teaching at the college level. Brings basic quantitative chemistry to treat ... Read full review

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Selected pages

Contents

Transcription Networks Basic Concepts
5
23 Elements of Transcription Networks
7
231 Separation of Timescales
9
Activators and Repressors
12
The Input Function
13
A Simple Framework for Understanding Network Dynamics
15
235 MultiDimensional Input Functions Govern Genes with Several Inputs
16
236 Interim Summary
18
72 Bacterial Chemotaxis or How Bacteria Think
136
722 Response and Exact Adaptation
137
73 The Chemotaxis Protein Circuit of E coli
140
731 Attractants Lower the Activity of X
141
732 Adaptation Is Due to Slow Modification of X That Increases Its Activity
142
741 FineTuned Model
143
742 The BarkaiLeibler Robust Mechanism for Exact Adaptation
146
743 Robust Adaptation and Integral Feedback
148

241 The Response Time of Stable Proteins Is One Cell Generation
21
Further Reading
22
Autoregulation A Network Motif
27
321 Detecting Network Motifs by Comparison to Randomized Networks
29
A Network Motif
30
34 Negative Autoregulation Speeds the Response Time of Gene Circuits
31
35 Negative Autoregulation Promotes Robustness To Fluctuations in Production Rate
34
351 Positive Autoregulation Slows Responses and Can Lead to BiStability
37
Exercises
38
The FeedForward Loop Network Motif
41
42 The Number of Appearances of a Subgraph in Random Networks
42
43 The FeedForward Loop is a Network Motif
45
44 The Structure of the FeedForward Loop Gene Circuit
46
45 Dynamics of the Coherent Type1 FFL with AND Logic
49
46 The C1FFL is a SignSensitive Delay Element
50
461 Delay Following an ON Step of Sx
51
462 No Delay Following an OFF Step of Sx
52
465 SignSensitive Delay in the Arabinose System of E coli
54
466 The OR Gate C1FFL Is a SignSensitive Delay for OFF Steps of Sx
56
47 The Incoherent Type1 FFL
57
A Pulse Generator
58
473 The I1FFL Speeds the Response Time
62
474 Response Acceleration Is Sign Sensitive
63
476 Three Ways to Speed Your Responses An Interim Summary
64
48 Why Are Some FFL Types Rare?
65
49 Convergent Evolution of FFLs
68
410 Summary
69
Further Reading
70
Exercises
71
Temporal Programs and the Global Structure of Transcription Networks
75
52 The SingleInput Module SIM Network Motif
76
53 SIMs Can Generate Temporals Expression Programs
77
54 Topological Generalizations of Network Motifs
81
55 The MultiOutput FFL Can Generate FIFO Temporal Order
83
551 The MultiOutput FFL Can Also Act as a Persistence Detector for Each Output
87
BiFlaws and Dense Overlapping Regulons
88
57 Network Motifs and the Global Structure of Sensory Transcription Networks
89
Further Reading
92
Exercises
93
Network Motifs in Developmental Signal Transduction and Neuronal Networks
97
62 Network Motifs in Developmental Transcription Networks
98
621 TwoNode Positive Feedback Loops for Decision Making
99
622 Regulating Feedback and Regulated Feedback
101
623 Long Transcription Cascades and Developmental Timing
102
63 Network Motif in Signal Transduction Networks
104
64 Information Processing Using MultiLayer Perceptrons
106
642 MultiLayer Perceptrons Can Perform Detailed Computations
111
Negative Feedback and Oscillator Motifs
115
66 Network Motifs in the Neuronal Network of C elegans
118
661 The MultiInput FFL in Neuronal Networks
122
662 MultiLayer Perceptrons in the C elegans Neuronal Network
125
67 Summary
127
Further Reading
128
Exercises
129
Robustness of Protein Circuits The Example of Bacterial Chemotaxis
135
744 Experiments Show That Exact Adaptation Is Robust Whereas SteadyState Activity and Adaptation Times Are FineTuned
149
Further Reading
151
Exercises
152
Robust Patterning in Development
159
82 Exponential Morphogen Profiles Are Not Robust
161
83 Increased Robustness by SelfEnhanced Morphogen Degradation
163
84 Network Motifs That Provide Degradation Feedback for Robust Patterning
165
85 The Robustness Principle Can Distinguish between Mechanisms of Fruit Fly Patterning
166
Further Reading
172
Kinetic Proofreading
175
92 Kinetic Proofreading of the Genetic Code Can Reduce Error Rates of Molecular Recognition
176
921 Equilibrium Binding Cannot Explain the Precision of Translation
177
922 Kinetic Proofreading Can Dramatically Reduce the Error Rate
180
93 Recognizing Self and NonSelf by the Immune System
182
931 Equilibrium Binding Cannot Explain the Low Error Rate of Immune Recognition
183
932 Kinetic Proofreading Increases Fidelity of TCell Recognition
185
94 Kinetic Proofreading May Occur in Diverse Recognition Processes in the Cell
187
Further Reading
188
Optimal Gene Circuit Design
193
102 Optimal Expression Level of a Protein Under Constant Conditions
194
021 The Benefit of the LacZ Protein
195
1022 The Cost of the LacZ Protein
196
1023 The Fitness Function and the Optimal Expression Level
197
1024 Laboratory Evolution Experiment Shows That Cells Reach Optimal LacZ Levels in a Few Hundred Generations
199
Optinal Regulation in Variable Environments
201
104 Environmental Selection of the FeedForward Loop Network Motif
203
105 Summary
207
Exercises
208
Demand Rules for Gene Regulation
215
112 The Savageau Demand Rule
217
1122 Mutational Explanation of the Demand Rule
219
1123 The Problem with MutantSelection Arguments
220
114 The Selection Pressure for Optimal Regulation
222
115 Demand Rules for MultiRegulator Systems
223
116 Summary
228
Further Reading
230
Epilogue Simplicity in Biology
233
The Input Function of a Gene MichaelisMenten and Hill Equations
241
MichaelisMenten Equation
244
A3 Cooperativity of Inducer Binding and the Hill Equation
245
A4 The Momod Changeux and Wymann Model
247
A6 Binding of an Activator to Its DNA Site
248
A61 Comparison of Dynamics with Logic and Hill Input Functions
250
Further Reading
251
MultiDimensional Input Functions
253
Exercises
255
Graph Properties of Transcription Networks
257
C3 Clustering Coefficients of Transcription Networks
259
D CellCell Variability in Gene Expression
261
Further Reading
264
GLOSSARY
265
BIBLIOGRAPHY
271
INDEX
295
Copyright

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An Introduction to Systems Biology: Design Principles of Biological Circuits
An Introduction to Systems Biology: Design Principles of Biological Circuits
Uri Alon
Limited preview - 2007

Common terms and phrases

activation threshold amino acid arabinose autoregulation bacteria binds the promoter biochemical Biol biological networks cascade cell Chapter CheB chemotaxis CheR codon coli complex concentration degradation degradation/dilution demand rule described dynamics edges environment enzyme Equation error rate error-load Escherichia coli exact adaptation example expression level feed-forward loop feedback loop FFL types Figure flagella gene circuits gene expression gene regulation genetic glucose growth rate Il-FFL increases input signal interactions IPTG kinase kinetic proofreading lac system lactose LacZ ligand mechanism methylation mode modules molecule morphogen mRNA multi-output FFL mutations negative autoregulation network motifs neuronal network neurons nodes occurs optimal output parameters pathway patterns phosphorylation production rate protein level random networks regulatory repression repressor response robust Savageau selection sensory transcription networks sign-sensitive delay signal Sx signal transduction simple regulation steady-state step of Sx stochastic subgraphs T-cell timescale tion transcription factor tRNA tumbling frequency

Popular passages

Page 279 - Exploring the new world of the genome with DNA microarrays.‎
Appears in 142 books from 1979-2008
Page 278 - Cohen. 2002. Global analysis of mRNA decay and abundance in Escherichia coli at single-gene resolution using two-color fluorescent DNA microarrays. Proc. Natl. Acad. Sci. USA 99:9697-9702.‎
Appears in 13 books from 1959-2007
Page 293 - On the roles of synthesis and degradation in regulation of enzyme levels in mammalian tissues. Curr. Top. Cell. Regul. 1, 77-124. Stadtman, ER (1970). Mechanisms of Enzyme Regulation. In "The Enzymes" (PD Boyer, ed.), 3rd ed., Vol.‎
Appears in 47 books from 1928-2006
Page 280 - Dolmetsch, RE, Xu, K. and Lewis, RS (1998). Calcium oscillations increase the efficiency and specificity of gene expression.‎
Appears in 31 books from 1869-2007

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References from web pages

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Bibliographic information

QR code for Introduction to Systems Biology
TitleIntroduction to Systems Biology: And the Design Principles of Biological Networks
Volume 10 of Chapman and Hall/CRC mathematical and computational biology series
AuthorUri Alon
Editionillustrated
PublisherCRC Press, 2007
ISBN1584886420, 9781584886426
Length301 pages
Subjects ›  › 

Mathematics / Applied
Mathematics / Probability & Statistics / General
Science / Biotechnology
Science / Physics / General
  
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