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PART II: BIOLOGICAL NETWORK MODELING
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PART II: BIOLOGICAL NETWORK MODELING
by Stephen H. Muggleton, Huma M. Lodhi
Elements of Computational Systems Biology
Cover Page
Title Page
Copyright
CONTENTS
PREFACE
CONTRIBUTORS
PART I: OVERVIEW
CHAPTER 1: ADVANCES IN COMPUTATIONAL SYSTEMS BIOLOGY
1.1 INTRODUCTION
1.2 MULTISCALE COMPUTATIONAL MODELING
1.3 PROTEOMICS
1.4 COMPUTATIONAL SYSTEMS BIOLOGY AND AGING
1.5 COMPUTATIONAL SYSTEMS BIOLOGY IN DRUG DESIGN
1.6 SOFTWARE TOOLS FOR SYSTEMS BIOLOGY
1.7 CONCLUSION
REFERENCES
PART II: BIOLOGICAL NETWORK MODELING
CHAPTER 2: MODELS IN SYSTEMS BIOLOGY: THE PARAMETER PROBLEM AND THE MEANINGS OF ROBUSTNESS
2.1 INTRODUCTION
2.2 MODELS AS DYNAMICAL SYSTEMS
2.3 THE PARAMETER PROBLEM
2.4 THE LANDSCAPES OF DYNAMICS
2.5 THE MEANINGS OF ROBUSTNESS
2.6 CONCLUSION
REFERENCES
CHAPTER 3: IN SILICO ANALYSIS OF COMBINED THERAPEUTICS STRATEGY FOR HEART FAILURE
3.1 INTRODUCTION
3.2 MATERIALS AND METHODS
3.3 RESULTS
3.4 DISCUSSION
ACKNOWLEDGMENT
3A.1 APPENDIX
REFERENCES
CHAPTER 4: RULE BASED MODELING AND MODEL REFINEMENT
4.1 KAPPA, BRIEFLY
4.2 REFINEMENT, PRACTICALLY
4.3 RULE-BASED MODELING
4.4 REFINEMENT, THEORETICALLY
4.5 CONCLUSION
REFERENCES
CHAPTER 5: A (NATURAL) COMPUTING PERSPECTIVE ON CELLULAR PROCESSES
5.1 NATURAL COMPUTING AND COMPUTATIONAL BIOLOGY
5.2 MEMBRANE COMPUTING
5.3 FORMAL LANGUAGES PRELIMINARIES
5.4 MEMBRANE OPERATIONS WITH PERIPHERAL PROTEINS
5.5 MEMBRANE SYSTEMS WITH PERIPHERAL PROTEINS
5.6 CELL CYCLE AND BREAST TUMOR GROWTH CONTROL
REFERENCES
CHAPTER 6: SIMULATING FILAMENT DYNAMICS IN CELLULAR SYSTEMS
6.1 INTRODUCTION
6.2 BACKGROUND: THE ROLES OF FILAMENTS WITHIN CELLS
6.3 EXAMPLES OF FILAMENT SIMULATIONS
6.4 OVERVIEW OF FILAMENT SIMULATION
6.5 CHANGING FILAMENT LENGTH
6.6 FORCES ON FILAMENTS
6.7 IMPOSING CONSTRAINTS
6.8 SOLVER
6.9 CONCLUSION
REFERENCES
PART III: BIOLOGICAL NETWORK INFERENCE
CHAPTER 7: RECONSTRUCTION OF BIOLOGICAL NETWORKS BY SUPERVISED MACHINE LEARNING APPROACHES
7.1 INTRODUCTION
7.2 GRAPH RECONSTRUCTION AS A PATTERN RECOGNITION PROBLEM
7.3 EXAMPLES
7.4 DISCUSSION
REFERENCES
CHAPTER 8: SUPERVISED INFERENCE OF METABOLIC NETWORKS FROM THE INTEGRATION OF GENOMIC DATA AND CHEMICAL INFORMATION
8.1 INTRODUCTION
8.2 MATERIALS
8.3 SUPERVISED NETWORK INFERENCE WITH METRIC LEARNING
8.4 ALGORITHMS FOR SUPERVISED NETWORK INFERENCE
8.5 DATA INTEGRATION
8.6 EXPERIMENTS
8.7 DISCUSSION AND CONCLUSION
REFERENCES
CHAPTER 9: INTEGRATING ABDUCTION AND INDUCTION IN BIOLOGICAL INFERENCE USING CF-INDUCTION
9.1 INTRODUCTION
9.2 LOGICAL MODELING OF METABOLIC FLUX DYNAMICS
9.3 CF-INDUCTION
9.4 EXPERIMENTS
9.5 RELATED WORK
9.6 CONCLUSION AND FUTURE WORK
ACKNOWLEDGMENTS
REFERENCES
CHAPTER 10: ANALYSIS AND CONTROL OF DETERMINISTIC AND PROBABILISTIC BOOLEAN NETWORKS
10.1 INTRODUCTION
10.2 BOOLEAN NETWORK
10.3 IDENTIFICATION OF ATTRACTORS
10.4 CONTROL OF BOOLEAN NETWORK
10.5 PROBABILISTIC BOOLEAN NETWORK
10.6 COMPUTATION OF STEADY STATES OF PBN
10.7 CONTROL OF PROBABILISTIC BOOLEAN NETWORKS
10.8 CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
CHAPTER 11: PROBABILISTIC METHODS AND RATE HETEROGENEITY
11.1 INTRODUCTION TO PROBABILISTIC METHODS
11.2 SEQUENCE EVOLUTION IS DESCRIBED USING MARKOV CHAINS
11.3 AMONG-SITE RATE VARIATION
11.4 DISTRIBUTION OF RATES ACROSS SITES
11.5 SITE-SPECIFIC RATE ESTIMATION
11.6 TREE RECONSTRUCTION USING AMONG-SITE RATE VARIATION MODELS
11.7 DEPENDENCIES OF EVOLUTIONARY RATES AMONG SITES
11.8 RELATED WORKS
REFERENCES
PART IV: GENOMICS AND COMPUTATIONAL SYSTEMS BIOLOGY
CHAPTER 12: FROM DNA MOTIFS TO GENE NETWORKS: A REVIEW OF PHYSICAL INTERACTION MODELS
12.1 INTRODUCTION
12.2 FUNDAMENTALS OF GENE TRANSCRIPTION
12.3 PHYSICAL INTERACTION ALGORITHMS
12.4 CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
CHAPTER 13: THE IMPACT OF WHOLE GENOME IN SILICO SCREENING FOR NUCLEAR RECEPTOR-BINDING SITES IN SYSTEMS BIOLOGY
13.1 INTRODUCTION
13.2 NUCLEAR RECEPTORS
13.3 THE PPAR SUBFAMILY
13.4 METHODS FOR IN SILICO SCREENING OF TRANSCRIPTION FACTOR-BINDING SITES
13.5 BINDING DATASET OF PPREs AND THE CLASSIFIER METHOD
13.6 CLUSTERING OF KNOWN PPAR TARGET GENES
13.7 CONCLUSION
ACKNOWLEDGMENTS
REFERENCES
CHAPTER 14: ENVIRONMENTAL AND PHYSIOLOGICAL INSIGHTS FROM MICROBIAL GENOME SEQUENCES
14.1 SOME BACKGROUND, MOTIVATION, AND OPEN QUESTIONS
14.2 A FIRST STATISTICAL GLIMPSE TO GENOMIC SEQUENCES
14.3 AN AUTOMATIC DETECTION OF CODON BIAS IN GENES
14.4 GENOMIC SIGNATURES AND A SPACE OF GENOMES FOR GENOME COMPARISON
14.5 STUDY OF METABOLIC NETWORKS THROUGH SEQUENCE ANALYSIS AND TRANSCRIPTOMIC DATA
14.6 FROM GENOME SEQUENCES TO GENOME SYNTHESIS: MINIMAL GENE SETS AND ESSENTIAL GENES
14.7 A CHROMOSOMAL ORGANIZATION OF ESSENTIAL GENES
14.8 VIRAL ADAPTATION TO MICROBIAL HOSTS AND VIRAL ESSENTIAL GENES
14A.1 APPENDIX
REFERENCES
PART V: SOFTWARE TOOLS FOR SYSTEMS BIOLOGY
CHAPTER 15: A LI B ABA : A TEXT MINING TOOL FOR SYSTEMS BIOLOGY
15.1 INTRODUCTION TO TEXT MINING
15.2 A LI B ABA AS A TOOL FOR MINING BIOLOGICAL FACTS FROM LITERATURE
15.3 COMPONENTS AND USAGE OF A LI B ABA
15.4 ALI BABA'S APPROACH TO TEXT MINING
15.5 RELATED BIOMEDICAL TEXT MINING TOOLS
15.6 CONCLUSIONS AND FUTURE PERSPECTIVES
ACKNOWLEDGMENTS
REFERENCES
CHAPTER 16: VALIDATION ISSUES IN REGULATORY MODULE DISCOVERY
16.1 INTRODUCTION
16.2 DATA TYPES
16.3 DATA INTEGRATION
16.4 VALIDATION APPROACHES
16.5 CONCLUSIONS
REFERENCES
CHAPTER 17: COMPUTATIONAL IMAGING AND MODELING FOR SYSTEMS BIOLOGY
17.1 BIOINFORMATICS
17.2 BIOIMAGE INFORMATICS OF HIGH-CONTENT SCREENING
17.3 CONNECTING BIOINFORMATICS AND BIOMEDICAL IMAGING
17.4 SUMMARY
ACKNOWLEDGMENTS
REFERENCES
INDEX
WILEY SERIES ON BIOINFORMATICS: COMPUTATIONAL TECHNIQUES AND ENGINEERING
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CHAPTER 2: MODELS IN SYSTEMS BIOLOGY: THE PARAMETER PROBLEM AND THE MEANINGS OF ROBUSTNESS
II
BIOLOGICAL NETWORK MODELING
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