Table Of Contents:

Part I: Introduction

Integrative Systems View Of Life: Perspectives From General Systems Thinking 3(30)

J. Yasha Kresh

Introduction 4(1)

General System Theory: The Laws of Integrated Wholes 5(1)

Systemic Principles of Cybernetics 6(3)

Biological Systematics: Understanding Whole Systems 9(8)

Systems Biology and Mathematical Modeling 17(4)

Emergence: Complex Adaptive Systems 21(5)

The Complex Systems in Systems Biology 26(7)

Part II: Complex Systems Science: The Basics

Methods and Techniques of Complex Systems Science: An Overview 33(82)

Cosma Rohilla Shalizi

Introduction 33(4)

Statistical Learning and Data-Mining 37(9)

Time-Series Analysis 46(17)

Cellular Automata 63(2)

Agent-Based Models 65(5)

Evaluating Models of Complex Systems 70(6)

Information Theory 76(5)

Complexity Measures 81(14)

Guide to Further Reading 95(20)

Nonlinear Dynamical Systems 115(26)

Joshua E. S. Socolar

Introduction 115(3)

Dynamical Systems in General 118(1)

Linear Systems and Some Basic Vocabulary 119(2)

Nonlinear Effects in Simple Systems 121(9)

Two Types of Complexity: Spatial Structure and Network Structure 130(6)

Discussion and Conclusions 136(5)

Biological Scaling And Physiological Time: Biomedical Applications 141(24)

Van M. Savage

Geoffrey B. West

A.P. Allen

J.H. Brown

B.J. Enquist

J.F. Gillooly

A.B. Herman

W.H. Woodruff

Introduction 142(4)

Model Description: Theory for the Origin of Scaling Relationships 146(7)

Biomedical Applications 153(5)

Discussion and Conclusions 158(7)

The Architecture of Biological Networks 165(18)

Stefan Wuchty

Erszebet Ravasz

Albert-Laszlo Barabasi

Introduction 165(1)

Basic Network Features 166(3)

Networks Models 169(3)

Biological Networks 172(4)

Conclusions 176(7)

Robustness in Biological Systems: A Provisional Taxonomy 183(28)

David C. Krakauer

A Fundamental Biological Dichotomy: Robustness and Evolvability 183(2)

Genotypic versus Environmental versus Functional Robustness 185(1)

Principles and Parameters of Robust Organization 185(5)

Case Studies of Robust Principles 190(11)

Awaiting a Synthesis of Robustness in Biological Systems 201(10)

Part III: Complex Adaptive Biosystems: A Multi-Scaled Approach

Section III.1: Complexity in Molecular Networks

Noise in Gene Regulatory Networks 211(16)

Juan M. Pedraza

Alexander van Oudenaarden

Introduction 211(1)

The Master Equation Approach 212(8)

The Langevin Approach 220(4)

Discussion and Conclusions 224(3)

Modeling RNA Folding 227(20)

Ivo L. Hofacker

Peter F. Stadler

Introduction 227(3)

RNA Secondary Structures and Their Prediction 230(2)

Neutral Networks in the Sequence Space 232(3)

Conserved RNA Structures 235(1)

Discussion 236(11)

Protein Networks 247(18)

Andreas Wagner

Introduction 247(1)

Large-Scale Approaches to Identify Protein Expression 248(5)

Identifying Protein Interactions 253(6)

Medical Applications 259(6)

Electronic Cell Environments: Combining Gene, Protein, and Metabolic Networks 265(18)

Pawan Dhar

Masaru Tomita

Introduction 265(1)

Biomedical Background 266(2)

Modeling and Simulation 268(9)

Future Work and Its Relevance to Biomedicine 277(6)

Section III.2: The Cell as a Complex System

Tensegrity, Dynamic Networks, and Complex Systems Biology: Emergence in Structural and Information Networks Within Living Cells 283(28)

Sui Huang

Cornel Sultan

Donald E. Ingber

Introduction: Molecular Biology and Complex System Sciences 284(3)

Complexity in Living Systems 287(1)

Model: Networks as the General Conceptual Framework 288(2)

Results 290(16)

Conclusion 306(5)

Spatiotemporal Dynamics Of Eukaryotic Gradient Sensing 311(22)

K.K. Subramanian

Atul Narang

Introduction 312(5)

Model and Simulation 317(10)

Future Work 327(6)

Patterning By EGF Receptor: Models From Drosophila Development 333(24)

Lea A. Goentoro

Stanislav Y. Shvartsman

Introduction 333(2)

Two Examples of EGFR Signaling in Fruit Fly Development 335(6)

Modeling and Computational Analysis of Autocrine and Paracrine Networks 341(8)

Conclusions and Outlook 349(8)

Section III.3: Developmental Biology and the Cardiac System

Developmental Biology: Branching Morphogenesis 357(18)

Sharon R. Lubkin

Introduction 357(3)

Previous Work 360(1)

Model 361(7)

Discussion and Conclusions 368(7)

Modeling Cardiac Function 375(34)

Raimond L. Winslow

Introduction 375(1)

Cellular Models 376(16)

Models of the Cardiac Ventricles 392(10)

Discussion and Conclusions 402(7)

Cardiac Oscillations and Arrhythmia Analysis 409(16)

Leon Glass

Introduction 409(3)

Two Arrhythmias with a Simple Mathematical Analysis 412(2)

Reentrant Arrhythmias 414(2)

Future Prospects 416(9)

Section III.4: The Immune System

How Distributed Feedbacks From Multiple Sensors Can Improve System Performance: Immunology and Multiple-Organ Regulation 425(12)

Lee A. Segel

Introduction 425(1)

Therapy as an Information-Yielding Perturbation 426(1)

Employing Information on Progress toward Multiple Goals to Regulate the Immune Response 427(4)

Cytokines 431(1)

Contending with Multiple Independent Goals 432(1)

Relevance to Biomedicine 433(4)

Appendix: Equations for the Mathematical model 435(2)

Microsimulation of Inducible Reorganization in Immunity 437(14)

Thomas B. Kepler

Introduction 437(3)

Model 440(4)

Results 444(3)

Discussion and Conclusion 447(4)

The Complexity of the Immune System: Scaling Laws 451(12)

Alan S. Perelson

Jason G. Bragg

Frederik W. Wiegel

Introduction 451(2)

Scaling Laws in Immunology 453(4)

Conclusions 457(6)

Section III.5: The Nervous System

Neurobiology and Complex Biosystem Modeling 463(20)

George N. Reeke Jr.

Neuronal Systems Dynamics 464(9)

Future Work and Relevance to Biomedicine 473(4)

Conclusions 477(6)

Modeling Spontaneous Episodic Activity in Developing Neuronal Networks 483(24)

Joel Tabak

John Rinzel

Introduction 484(1)

Spontaneous Activity in Developing Networks 484(3)

Model of Spontaneous Activity in the Embryonic Chick Spinal Cord 487(3)

Properties and Applications of the Model 490(10)

Discussion and Future Work 500(7)

Clinical Neuro-Cybernetics: Motor Learning In Neuronal Systems 507(30)

Florian P. Kolb

Dagmar Timmann

Introduction 507(5)

Experimental Approaches and Behavioral Data 512(10)

Theoretical Approaches 522(7)

Relevance for Patients and Therapy 529(8)

Section III.6: Cancer: A Systems Approach

Modeling Cancer as a Complex Adaptive System: Genetic Instability and Evolution 537(20)

Kenneth J. Pienta

Introduction 537(1)

Cancer Risk in the Context of an Evolutionary Paradigm 538(2)

Cancer Evolution in the Context of Recent Human Evolution 540(4)

Modeling Cancer as a Complex Adaptive System at the Level of the Cell 544(7)

Conclusion: Applying Complexity Theory toward a Cure for Cancer 551(6)

Spatial Dynamics In Cancer 557(16)

Ricard V. Sole

Isabel Gonzalez Garcia

Jose Costa

Introduction 557(2)

Population Dynamics 559(1)

Competition in Tumor Cell Populations 560(3)

Competition with Spatial Dynamics 563(2)

Metapopulation Dynamics and Cancer Heterogeneity 565(4)

Discussion 569(4)

Modeling Tumors as Complex Biosystems: An Agent-Based Approach 573(32)

Yuri Mansury

Thomas S. Deisboeck

Introduction 573(3)

Previous Works 576(3)

Mathematical Model 579(7)

Specifications of the Model 586(3)

Basic Model Setup 589(3)

Results 592(5)

Discussion, Conclusions, and Future Work 597(8)

Section III.7: The Interaction of Complex Biosystems

The Complexity of Dynamic Host Networks 605(26)

Steve W. Cole

Introduction 605(1)

Model 606(1)

Results 607(14)

Discussion and Conclusions 621(10)

Appendix 622(9)

Physiologic Failure: Multiple Organ Dysfunction Syndrome 631(10)

Timothy G. Buchman

Introduction 631(2)

Previous Work 633(2)

Model 635(1)

Results 636(1)

Implications for Treatment 637(1)

Summary and Perspective 638(3)

Aging as a Process of Complexity Loss 641(16)

Lewis A. Lipsitz

Introduction 641(2)

Measures of Complexity Loss 643(3)

Examples of Complexity Loss with Aging 646(2)

Mechanisms of Physiologic Complexity 648(1)

Loss of Complexity as a Pathway to Frailty in Old Age 649(1)

Interventions to Restore Complexity in Physiologic Systems 650(2)

Conclusion 652(5)

Part IV: Enabling Technologies

Biomedical Microfluidics and Electrokinetics 657(22)

Steve Wereley

Carl Meinhart

Introduction 658(1)

DC Electrokinetics 659(4)

AC Electrokinetics 663(8)

Experimental Measurements of Electrokinetics 671(4)

Conclusions 675(4)

Gene Selection Strategies In Microarray Expression Data: Applications To Case-Control Studies 679(22)

Gustavo A. Stolovitzky

Introduction 679(2)

Previous Work: Gene Selection Methods in Microarray Data 681(4)

Combining Selection Methods Produces a Richer Set of Differentially Expressed Genes 685(5)

Gene Expression Arrays Can Be Used for Diagnostics: A Case Study 690(5)

Discussion and Conclusions 695(6)

Application of Biomolecular Computing to Medical Science: A Biomolecular Database System For Storage, Processing, and Retrieval of Genetic Information and Material 701(36)

John H. Reif

Michael Hauser

Michael Pirrung

Thomas LaBean

Introduction 702(4)

Review of Biotechnologies for Genomics and the Biomolecular Computing Field 706(3)

A Biomolecular Database System 709(16)

Applying Our Biomolecular Database System to Execute Genomic Processing 725(4)

Discussion and Conclusions 729(8)

Tissue Engineering: Multiscaled Representation Of Tissue Architecture And Function 737(26)

Mohammad R. Kaazempur-Mofrad

Eli J. Weinberg

Jeffrey T. Borenstein

Joseph P. Vacanti

Introduction 737(4)

Tissue-Engineering Investigations at Various Length Scales 741(14)

Continuing Efforts in tissue Engineering 755(2)

Conclusion 757(6)

Imaging the Neural Systems for Motivated Behavior and Their Dysfunction in Neuropsychiatric Illness 763(48)

Hans C. Breiter

Gregory P. Gasic

Nikos Makris

Introduction 764(2)

In Vivo Measurement of Human Brain Activity Using fMRI 766(4)

Theoretical Model of Motivation Function 770(6)

Neuroimaging of the General Reward/Aversion System Underlying Motivated Behavior 776(11)

Implications of Reward/Aversion Neuroimaging for Psychiatric Illness 787(4)

Linking the Distributed Neural Groups Processing Reward/Aversion Information to the Gene Networks that Establish and Modulate Their Function 791(20)

A Neuromorphic System 811(16)

David P. M. Northmore

John Moses

John G. Elias

Introduction: Artificial Nervous Systems 811(1)

The Neuron and the Neuromorph 812(2)

Hardware System 814(2)

Neuromorphs in a Winnerless Competition Network 816(2)

Sensorimotor Development in a Neuromorphic Network 818(1)

Simulated Network 819(5)

Neuromorphs in Neural Prosthetics 824(1)

Conclusions 824(3)

A Biologically Inspired Approach Toward Autonomous Real-World Robots 827(10)

Frank Kirchner

Dirk Spenneberg

Introduction 827(1)

Mechatronics 828(2)

Ambulation Control 830(2)

Results 832(2)

Discussion and Outlook 834(3)

Virtual Reality, Intraoperative Navigation, and Telepresence Surgery 837(12)

M. Peter Heilbrun

Introduction 838(1)

Biomedical Background 838(5)

The Future 843(3)

Discussion and Conclusions 846(3)
Index 849