00_fm_4774.qxd 1/22/07 3:13 PM Page i Systems Bioinformatics An Engineering Case-Based Approach 00_fm_4774.qxd 1/22/07 3:13 PM Page ii DISCLAIMER OF WARRANTY The technical descriptions, procedures, and computer programs in this book have been developed with the greatest of care and they have been useful to the authors in a broad range of applications; however, they are provided as is, without warranty of any kind. Artech House, Inc., and the authors and editors of the book titled Systems Bioinformatics: An Engineering Case-Based Approach make no warranties, express or implied, that the equations, programs, and procedures in this book or its associated software are free of error, or are consistent with any particular standard of merchantability. They should not be relied upon for solving a problem whose incorrect solution could result in injury to a person or loss of property. Any use of the programs or procedures in such a manner is at the user’s own risk. The editors, authors, and publisher disclaim all liability for direct, incidental, or consequent damages resulting from use of the programs or procedures in this book or the associated software. The Artech House Bioinformatics & Biomedical Imaging Series Steven Wong, Harvard Medical School, and Guang-Zhong Yang, Imperial College, Series Editors For a listing of recent related Artech House titles, please turn to the back of this book. 00_fm_4774.qxd 1/22/07 3:13 PM Page iii Systems Bioinformatics An Engineering Case-Based Approach Gil Alterovitz Marco F. Ramoni Editors artechhouse.com 00_fm_4774.qxd 1/22/07 3:13 PM Page iv Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the U.S. Library of Congress. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. 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Use of a term in this book should not be regarded as affecting the validity of any trademark or service mark. 10987654321 00_fm_4774.qxd 1/22/07 3:13 PM Page v To our parents 00_fm_4774.qxd 1/22/07 3:13 PM Page vi 00_fm_4774.qxd 1/22/07 3:13 PM Page vii Contents Preface xv PART I Introduction: Molecular and Cellular Biology 1 CHAPTER 1 Molecular and Cellular Biology: An Engineering Perspective 3 1.1 Cellular Structures and Functions 3 1.2 Introduction to Information Handling in Cells 4 1.3 The Importance and Diversity of Proteins 5 1.4 DNA Replication: Copying the Code 6 1.5 Transcription: Sending a Messenger 7 1.6 Translation: Protein Synthesis 9 1.7 Control of Gene Expression 11 1.8 Genetic Engineering 12 1.9 Summary 13 CHAPTER 2 Proteomics: From Genome to Proteome 15 2.1 Defining the Proteome 15 2.1.1 From Genes to Proteins 15 2.1.2 What Is Proteomics? 17 2.1.3 Functional Proteomics 18 2.2 Building Gene Collections for Functional Proteomics Approaches 18 2.2.1 Selection of Target Genes for a Cloning Project 21 2.2.2 Clone Production 25 2.2.3 Sequencing and Analysis 32 2.2.4 Clone Maintenance and Distribution 34 2.3 Use of Clones in Functional Proteomics Approaches 35 2.3.1 High-Throughput Protein Production 36 2.3.2 Protein Arrays 38 2.3.3 Cell-Based Functional Proteomic Assays 39 vii 00_fm_4774.qxd 1/22/07 3:13 PM Page viii viii Contents PART II Analysis: Signal Processing 47 CHAPTER 3 Introduction to Biological Signal Processing at the Cell Level 49 3.1 Introduction to Fundamental Signal Processing Concepts 51 3.1.1 Signals 51 3.1.2 Systems 54 3.1.3 Random Processes and Spectral Analysis 57 3.2 Signal Detection and Estimation 59 3.2.1 DNA Sequencing 60 3.2.2 Gene Identification 67 3.2.3 Protein Hotspots Identification 71 3.3 System Identification and Analysis 74 3.3.1 Gene Regulation Systems 77 3.3.2 Protein Signaling Systems 84 3.4 Conclusion 93 CHAPTER 4 Signal Processing Methods for Mass Spectrometry 101 4.1 Introduction 101 4.1.1 Data Acquisition Methods 102 4.1.2 History of Ionization Techniques 102 4.1.3 Sample Preparation 103 4.1.4 Ionization 103 4.1.5 Separation of Ions by Mass and Charge 103 4.1.6 Detection of Ions and Recorded Data 104 4.1.7 Data Preprocessing 104 4.1.8 Example Data 105 4.2 Signal Resampling 105 4.2.1 Algorithm Explanation and Discussion 106 4.2.2 Example Demonstrating Down Sampling 107 4.3 Correcting the Background 109 4.3.1 Algorithm Explanation and Discussion 109 4.3.2 Example Demonstrating Baseline Subtraction 111 4.4 Aligning Mass/Charge Values 112 4.4.1 Algorithm Explanation and Discussion 113 4.4.2 Example Demonstrating Aligning Mass/Charge Values 114 4.5 Normalizing Relative Intensity 116 4.5.1 Example Demonstrating Intensity Normalization 116 4.6 Smoothing Noise 119 4.6.1 Lowess Filter Smoothing 120 4.6.2 Savitzky and Golay Filter Smoothing 121 4.6.3 Example Demonstrating Noise Smoothing 121 4.7 Identifying Ion Peaks 122 00_fm_4774.qxd 1/22/07 3:13 PM Page ix Contents ix PART III Analysis: Control and Systems 125 CHAPTER 5 Control and Systems Fundamentals 127 5.1 Introduction 127 5.2 Review of Fundamental Concepts in Control and Systems Theory 128 5.2.1 Discrete-Time Dynamical Systems 132 5.3 Control Theory in Systems Biology 133 5.4 Reverse Engineering Cellular Networks 135 5.5 Gene Networks 137 5.5.1 Boolean Networks 139 5.5.2 Dynamic Bayesian Networks 143 5.6 Conclusion 147 CHAPTER 6 Modeling Cellular Networks 151 6.1 Introduction 151 6.2 Construction and Analysis of Kinetic Models 153 6.2.1 Parameter Estimation and Modeling Resources 153 6.2.2 A Modular Approach to Model Formulation 154 6.2.3 Basic Kinetics 156 6.2.4 Deterministic Models 158 6.2.5 Cellular Noise and Stochastic Methods 158 6.2.6 System Analysis Techniques 161 6.3 Case Studies 164 6.3.1 Expression of a Single Gene 164 6.3.2 A Phosphorylation-Dephosphorylation Cycle 166 6.3.3 A Synthetic Population Control Circuit 168 6.4 Conclusion 172 PART IV Analysis: Probabilistic Data Networks and Communications 179 CHAPTER 7 Topological Analysis of Biomolecular Networks 181 7.1 Cellular Networks 181 7.1.1 Genetic Regulation Networks 182 7.1.2 Protein-Protein Interaction Networks 184 7.1.3 Metabolic Regulation Networks 185 7.1.4 The Scale-Free Property: A Network Characteristic 186 7.2 The Topology of Cellular Networks 189 7.2.1 Network Motifs in Genetic Regulation Networks 189 7.2.2 Topological Characterization of Protein Networks 191 7.2.3 Topology of Metabolic Networks 192 00_fm_4774.qxd 1/22/07 3:13 PM Page x x Contents 7.2.4 Adjacency Matrices 196 7.2.5 Hubs 196 7.2.6 Reachability 197 7.3 Gene Ontology and Functional Clustering of Essential Genes 198 7.4 Conclusion and Future Avenues 201 CHAPTER 8 Bayesian Networks for Genetic Analysis 205 8.1 Introduction 205 8.2 Elements of Population Genetics 206 8.3 Bayesian Networks 210 8.3.1 Representation 210 8.3.1 Learning 213 8.3.3 Reasoning 217 8.3.4 Validation and Inference 219 8.3.5 Risk Prediction 219 8.4 Two Applications 221 8.4.1 Stroke Risk in Sickle Cell Anemia Subjects 221 8.4.2 Network Representation of a Complex Trait 221 8.5 Conclusion 224 PART V Design: Synthetic Biology 229 CHAPTER 9 Fundamentals of Design for Synthetic Biology 231 9.1 Overview 231 9.2 Circuits 232 9.2.1 Riboregulators 234 9.2.2 Feedback Loops 235 9.2.3 Toggle Switches 236 9.2.4 Logic Gates 236 9.2.5 Oscillators 236 9.3 Multicellular Systems 236 9.4 Challenges 238 9.4.1 Standardization 238 9.4.2 Stochasticity 238 9.4.3 Directed Evolution 239 9.4.4 Random and Targeted Mutagenesis and Recombination 239 9.4.5 System Interface 240 9.4.6 Kinetics 240 9.5 Conclusion 240 00_fm_4774.qxd 1/22/07 3:13 PM Page xi Contents xi CHAPTER 10 BioJADE: Designing and Building Synthetic Biological Systems from Parts 243 10.1 Introduction 243 10.2 Fundamentals of BioJADE and BioBricks Construction 243 10.2.1 Inspiration 243 10.2.2 The BioBricks Standard 244 10.2.3 BioBrick Definition 244 10.2.4 The Abstraction Barrier 245 10.3 Representing Parts 246 10.3.1 Parts Data Model 247 10.4 BioJADE Architecture 248 10.4.1 Aspects 248 10.4.2 Schematic 249 10.4.3 Functional Network Aspect 250 10.4.4 DNA Aspect 250 10.4.5 Icon Aspect 251 10.4.6 Part Repositories 251 10.5 Using BioJADE, an Example: The Repressilator 251 10.6 Simulations 254 10.6.1 D-FLUX 254 10.6.2 Stochastirator 255 10.6.3 Tabasco 255 10.6.4 Generating the Simulation 256 10.7 The Reality Check 257 10.7.1 Biological Circuit Design Cannot Be as Easy as VLSI Design 257 10.7.2 Bugs Fight Back 257 10.8 Next Steps 258 10.8.1 Simulations 258 10.8.2 Parts 259 10.8.3 Designing Systems 259 10.8.4 Measurement 259 CHAPTER 11 Applied Cellular Engineering 263 11.1 Introduction 263 11.1.1 Biological Systems Engineering 263 11.1.2 Cellular Catalytic Machinery 265 11.1.3 Early Engineering Successes 265 11.2 Engineering Tools 266 11.2.1 Network Models and Analysis 266 11.2.2 Experimental Methods 271 11.3 Case Study: Production of 1,3-Propanediol in E.