Biophysics Books
Springer Microanalysis of Solids
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Springer A Manual of Applied Techniques for Biological Electron Microscopy
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Springer Fatigue Neural and Muscular Mechanisms 384 Advances in Experimental Medicine and Biology
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Springer Basic and Clinical Perspectives in Vision Research A Celebration of the Career of Hisako Ikeda
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Springer Current Research in Sports Sciences An International Perspective Advances in Experimental Medicine Biology Springer
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Springer Bioengineering Approaches to Pulmonary Physiology and Medicine
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Springer Fluorescence Microscopy and Fluorescent Probes
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Springer Optical Imaging of Brain Function and Metabolism 2 Physiological Basis and Comparison to Other Functional Neuroimaging Methods 413 Advances in Experimental Medicine and Biology 413
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Springer Acoustical Signal Processing in the Central Auditory System Proceedings of an International Symposium Held in Prague Czech Republic September 47 1996 Language of Science
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Springer Plant Cold Hardiness Molecular Biology Biochemistry and Physiology
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Springer fluorescencemicroscopyandfluorescentprobes
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Springer Gene Therapy of Cancer
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Springer Electricity and Magnetism in Biology and Medicine
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Springer Oxygen Transport to Tissue XXI
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Springer Atomic Force MicroscopyScanning Tunneling Microscopy 3
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Springer A Monte Carlo Primer A Practical Approach to Radiation Transport
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Springer Oxygen Transport To Tissue XXIII
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Springer Science+Business Media Scanning Electron Microscopy of Cerebellar Cortex
Book SynopsisIn a clear exposition this inspirational book shows the in situ three-dimensional morphology of cerebellar neurons, intracortical circuits and synaptic connections that underpin the functioning of cerebellar neurons in networks. It brings together in one volume a new view of the three-dimensional cytoarchitectonic arrangement of the cerebellar cortex. The book shows the cerebellar extrinsic and intrinsic intracortical circuits formed by mossy and climbing fibers as exposed by the cryofracture methods. The high degree of lateral collateralization of these fibers is also displayed providing new insights on the information processing in the cerebellar cortex. Besides, field emission high resolution electron microscopy shows its potential contribution to the study of synaptic morphology. The concluding chapter deals with the contribution of scanning electron microTable of ContentsI: Sample Preparation Methods for Scanning Electron Microscopy. Introduction. Conventional SEM technique or slicing technique. Fixation procedures. The prefixation state of nerve tissue. Vascular perfusion fixation technique. Criteria for good fixation and optimal preservation of nerve tissue. Trimming procedure and obtaining nerve tissue slices. Dehydration. Critical point drying (CPD) method. Specimen mounting and orientation. Metal deposition. Special SEM preparation techniques. Concluding remarks. II: The Cerebellar White Matter. Brief history. The afferent and efferent fibers. Concluding remarks.
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Springer Biological Electron Microscopy
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Springer EPR Instrumental Methods
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Springer Calcium Channel Pharmacology
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Springer Oxygen Transport to Tissue XXV
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Springer Supramolecular Structure and Function 8 Bioengineering Mechanics and Materials Principles and Applications in Sport Bioengineering Mechanics Principles and Applications in Sport S
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Elsevier Science Essentials of Medical Biochemistry
Book SynopsisTable of Contents1. The Human Organism: Organ Systems, Cells, Organelles, and Our Microbiota 2. Water, Acids, Bases, and Buffers 3. Amino Acids 4. Three-Dimensional Structure of Proteins and Disorders of Protein Misfolding 5. Energetics of Biological Systems, Enzymes and Enzyme Regulation 6. Clinical Enzymology and Biomarkers of Tissue Injury 7. Simple Carbohydrates 8. Heteropolysaccharides: Glycoconjugates, Glycoproteins, and Glycolipids 9. Connective Tissue: Fibrous and Nonfibrous Proteins and Proteoglycans 10. Gastrointestinal Digestion and Absorption 11. Carbohydrate Metabolism I: Glycolysis and the Tricarboxylic Acid Cycle 12. Electron Transport Chain, Oxidative Phosphorylation, and Other Oxygen-Consuming Systems 13. Carbohydrate Metabolism II: Gluconeogenesis, Glycogen Synthesis and Breakdown, and Alternative Pathways 14. Protein and Amino Acid Metabolism 15. Lipids I: Fatty Acids and Eicosanoids 16. Lipids II: Phospholipids, Glycosphingolipids, and Cholesterol 17. Lipids III: Plasma Lipoproteins 18. Contractile Systems 19. Perturbations of Energy Metabolism: Obesity and Diabetes Mellitus 20. Structure and Properties of DNA 21. DNA Replication, Repair, and Mutagenesis 22. RNA and Protein Synthesis 23. Regulation of Gene Expression 24. Nucleotide Metabolism 25. Hemoglobin and Metabolism of Iron & Heme 26. Endocrine Metabolism I: Introduction and Signal Transduction 27. Endocrine Metabolism II: Hypothalamus and Pituitary 28. Endocrine Metabolism III: Adrenal Glands 29. Endocrine Metabolism IV: Thyroid Gland 30. Endocrine Metabolism V: Reproductive System 31. Immunology 32. Biochemistry of Hemostasis 33. Mineral Metabolism 34. Vitamin Metabolism 35. Drug Metabolism
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Elsevier Science Hormones
Book SynopsisTable of Contents1. Introduction 2. Steroid Hormones: Chemistry, Biosynthesis, and Metabolism 3. The Hypothalamus and Anterior Pituitary 4. Posterior Pituitary Hormones 5. Thyroid Hormones 6. Pancreatic Hormones: Insulin and Glucagon 7. Gastrointestinal Hormones 8. Eicosanoids 9. Calcium-Regulating Hormones: Vitamin D, Parathyroid Hormone, Calcitonin & Fibroblast Growth Factor-23 10. Adrenal Corticoids 11. Hormones of the Adrenal Medulla 12. Androgens 13. Estrogens and Progestins 14. Hormones of Pregnancy, Parturition and Lactation 15. Hormones Related to the Kidney and Cardiovascular System 16. The Pineal Gland 17. Growth Factors
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Biosurfactants
Book SynopsisTable of ContentsSection I Introduction 1. Microbial bio-based amphiphiles (biosurfactants): General aspects on critical micelle concentration, surface tension, and phase behavior 2. New insights in biosurfactants Research Section II Novel approaches for the production and use of biosurfactants 3. Bioinspired glycolipids: Metals interactions and aqueous-source metal recovery technologies 4. Rhamnolipids—Has the promise come true? 5. Biosurfactants as food additives: New trends and applications 6. Novel approaches in the use of biosurfactants in the oil industry and environmental remediation 7. Biosurfactants produced from corn steep liquor and other nonconventional sources: Their application in different industries Section III Genetic manipulation and the production of novel biosurfactants 8. Metabolic and process engineering on the edge—Rhamnolipids are a true challenge: A review 9. Improved production of novel (bola) glycolipid biosurfactants with the yeast Starmerella bombicola through an integrative approach combining genetic engineering and multiomics analyses 10. Increasing the natural biodiversity of microbial lipopeptides using a synthetic biology approach Section IV Use of alternative strategies for biosurfactants production 11. Synthetic approaches to production of rhamnolipid and related glycolipids 12. The use of biocatalysis for biosurfactant production Section V Concluding remarks 13. Challenges and prospects for microbial biosurfactant research
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Elsevier Science Electromagnetic WavesBased Cancer Diagnosis and
Book SynopsisTable of Contents1. Radio Wave-Involved Cancer Therapy and Imaging 2. Cancer Therapy by Microwaves Hyperthermia 3. Application of Infra-Red Waves in Cancer Theranostic 4. Usage of Visible Light in Cancer Diagnosis (Endoscopy) 5. X-ray Based Cancer Treatment Methods 6. Gamma ray-Involved Cancer Therapy and Imagin
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Taylor & Francis Ltd Structural and Morphological Evolution in MetalOrganic Films and Multilayers
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Taylor & Francis Ltd Spike Timing Mechanisms and Function 53 Frontiers in Neuroscience
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Taylor & Francis Ltd Fluctuation Theory of Solutions
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Taylor & Francis Ltd Chemical Physics Electrons and Excitations
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Taylor & Francis Ltd Proteins Energy Heat and Signal Flow 01 Computation in Chemistry
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Taylor & Francis Ltd Textbook of Ion Channels Volume I
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Taylor & Francis Ltd Textbook of Ion Channels Volume II
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Taylor & Francis Ltd Textbook of Ion Channels Volume III
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Taylor & Francis Ltd Imaging from Cells to Animals In Vivo
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Taylor & Francis Ltd RNA the Epicenter of Genetic Information
Book SynopsisThe origin story and emergence of molecular biology is muddled. The early triumphs in bacterial genetics and the complexity of animal and plant genomes complicate an intricate history. This book documents the many advances, as well as the prejudices and founder fallacies. It highlights the premature relegation of RNA to simply an intermediate between gene and protein, the underestimation of the amount of information required to program the development of multicellular organisms, and the dawning realization that RNA is the cornerstone of cell biology, development, brain function and probably evolution itself. Key personalities, their hubris as well as prescient predictions are richly illustrated with quotes, archival material, photographs, diagrams and references to bring the people, ideas and discoveries to life, from the conceptual cradles of molecular biology to the current revolution in the understanding of genetic information.Key Features Documents the confused early history of DNA, RNA and proteins - a transformative history of molecular biology like no other. Integrates the influences of biochemistry and genetics on the landscape of molecular biology. Chronicles the important discoveries, preconceptions and misconceptions that retarded or misdirected progress. Highlights major pioneers and contributors to molecular biology, with a focus on RNA and noncoding DNA. Summarizes the mounting evidence for the central roles of non-protein-coding RNA in cell and developmental biology. Provides a thought-provoking retrospective and forward-looking perspective for advanced students and professional researchers. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.Trade Review“Thrilling and provocative ... There is a need for such a book... There’s nothing quite like this out there.An epic tale of biology’s central molecule, RNA.DNA does only one thing, store information. RNA has a thrilling plethora of functions, including telling DNA what to do. This book takes the reader on an odyssey through the wonders of RNA and its central role in biology.DNA science dominated the second half of the 20th Century, but it’s clear that the 21st Century belongs to RNA. This long-overdue book reveals the diverse wonders of RNA in a series of thrilling and provocative stories.”Tom Cech, Nobel laureate, University of Colorado Boulder_____________________________________“The book is truly monumental and will be treasured by RNA scientists and others, as well. It beautifully captures the excitement and wonder that I have been lucky to experience working in the RNA field since the early 1960s.”Joan Steitz, Yale University_____________________________________“This book is really disruptive and presents a coherent view of our understanding of biology in terms of the genetic molecules, the nucleic acids, DNA and RNA. It covers an immense territory of molecular biology and its history of discoveries, all presented with a clear-cut intellectual thread.... It is very timely by its breadth and emphasis on the role of RNA in biology. It makes a strong case for RNA and its late acceptance... the fight uphill, like that of Sisyphus, was tough and demanded a lot of perseverance. It is really rather complete.”Eric Westhof, University of Strasbourg_____________________________________“The book is unique. It provides the long-overdue correction of the still widespread static views on evolution, development and genome organization and function. It has the potential to induce radical changes in widely held views and attitudes.”Peter Vogt, Scripps Research Institute, La Jolla_____________________________________"History is the key to our modern understanding of RNA. This magnum opus describes how science, scientific thought and landmark discoveries revealed the central role of RNA in molecular biology and evolution. The authors are not only modern pioneers of RNA science, but also the best histo-RNA-ians of our time.”John Rinn, University of Colorado, Boulder_____________________________________"RNA, the Epicenter of Genetic Information is much more than what its title might suggest. This epic book by Mattick and Amaral superbly reflects the continuing excitement about RNA research. It is not only a description of our current understanding of the role of RNA in cell and developmental biology but is also a useful history of molecular biology. Each of the eighteen chapters is a brilliantly written semi-autonomous essay on a particular segment of the RNA odyssey. I wholeheartedly recommend this book to anybody interested in the biology of RNA, in evolution, and in the organization and function of complex genomes." Witold Filipowicz, Friedrich Miescher Institute for Biomedical Research, Basel_____________________________________"Those who might think that this book is only for the scientists, think again. It is not. It will appeal in equal measure to the thinking generalist and culturally curious interested in the thrilling history of molecular biology, the wonders of the long-overlooked central molecule RNA and its pivotal role in human development and evolution.An epic, provocative, and highly original book that highlights the way science is so often sidetracked by preconceptions and hubris, and explores the struggle to understand all that junk DNA we were told we had. The junk is not junk! The answers are all there. A story and a journey not to be missed!"Gabriel Farago (USA TODAY Bestselling author of the Jack Rogan Mysteries Series) Table of ContentsPreface, Chapter 1. Overview, Chapter 2. The genetic material?, Chapter 3. Halcyon days, Chapter 4. Worlds apart, Chapter 5. Strange genomes, strange genetics, Chapter 6. The Age of Aquarius, Chapter 7. All that junk, Chapter 8. The expanding repertoire of RNA, Chapter 9. Glimpses of a modern RNA world, Chapter 10. Genome sequences and transposable elements, Chapter 11. The human genome, Chapter 12. Small RNAs with mighty functions, Chapter 13. Large RNAs with many functions, Chapter 14. The epigenome, Chapter 15. The programming of development, Chapter 16. RNA and repeats rule, Chapter 17. Plasticity, Chapter 18. Beyond the jungle of dogmas, References
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Taylor & Francis Ltd Molecular Modeling at the Atomic Scale
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Taylor & Francis Ltd Introduction to Molecular Biophysics
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Taylor & Francis Ltd Ventilation of Normobaric and Hyperbaric Objects
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Taylor & Francis Ltd Metabolism and Medicine
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Taylor & Francis Ltd Metabolism and Medicine
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Taylor & Francis Ltd Science of Diving Concepts and Applications
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Taylor & Francis Ltd Nonequilibrium Statistical Mechanics
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Taylor & Francis Ltd An Introduction to Computational Systems Biology
Book SynopsisThis book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networksa fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuringTrade ReviewThis is a very comprehensive read that provides a solid base in computational biology. The book is structured in 4 parts and 14 chapters which cover all the way from the more basic concepts to advanced material, including the state-of-the-art methodologies in synthetic and systems biology. This is a bedside book for those researchers embarking to do investigation in computational biology and a great office companion for anyone working on systems and synthetic biology. -- Rodrigo Ledesma Amaro, Lecturer, Imperial College London This is a fantastic book. It offers an elegant introduction to both classical and modern concepts in computational biology. To the uninitiated, it is a terrific first read, bringing alive the glory of the past and the promise of the future. To the interested, it handholds and offers a springboard to dive deep. To the practitioner, it serves as a valuable resource bringing together in a panoramic view many diverse streams that adorn the landscape. -- Narendra M. Dixit, Professor, Indian Institute of Science This is a very comprehensive read that provides a solid base in computational biology. The book is structured in 4 parts and 14 chapters which cover all the way from the more basic concepts to advanced material, including the state-of-the-art methodologies in synthetic and systems biology. This is a bedside book for those researchers embarking to do investigation in computational biology and a great office companion for anyone working on systems and synthetic biology. -- Rodrigo Ledesma Amaro, Lecturer, Imperial College London This is a fantastic book. It offers an elegant introduction to both classical and modern concepts in computational biology. To the uninitiated, it is a terrific first read, bringing alive the glory of the past and the promise of the future. To the interested, it handholds and offers a springboard to dive deep. To the practitioner, it serves as a valuable resource bringing together in a panoramic view many diverse streams that adorn the landscape. -- Narendra M. Dixit, Professor, Indian Institute of Science Table of ContentsPreface Introduction to modelling 1.1 WHAT IS MODELLING? 1.1.1 What are models? 1.2 WHYBUILD MODELS? 1.2.1 Why model biological systems? 1.2.2 Why systems biology? 1.3 CHALLENGES IN MODELLING BIOLOGICAL SYSTEMS 1.4 THE PRACTICE OF MODELLING 1.4.1 Scope of the model1.4.2 Making assumptions 1.4.3 Modelling paradigms 1.4.4 Building the model 1.4.5 Model analysis, debugging and (in)validation 1.4.6 Simulating the model 1.5 EXAMPLES OF MODELS 1.5.1 Lotka–Volterra predator–prey model 1.5.2 SIR model: a classic example 1.6 TROUBLESHOOTING 1.6.1 Clarity of scope and objectives 1.6.2 The breakdown of assumptions 1.6.3 Ismy model fit for purpose? 1.6.4 Handling uncertainties EXERCISES REFERENCES FURTHER READING Introduction to graph theory 2.1 BASICS 2.1.1 History of graph theory 2.1.2 Examples of graphs 2.2 WHYGRAPHS? 2.3 TYPES OF GRAPHS 2.3.1 Simple vs. non-simple graphs 2.3.2 Directed vs. undirected graphs 2.3.3 Weighted vs. unweighted graphs 2.3.4 Other graph types 2.3.5 Hypergraphs 2.4 COMPUTATIONAL REPRESENTATIONS OF GRAPHS 2.4.1 Data structures 2.4.2 Adjacency matrix 2.4.3 The laplacian matrix 2.5 GRAPH REPRESENTATIONS OF BIOLOGICAL NETWORKS 2.5.1 Networks of protein interactions and functional associations2.5.2 Signalling networks 2.5.3 Protein structure networks 2.5.4 Gene regulatory networks 2.5.5 Metabolic networks 2.6 COMMONCHALLENGES&TROUBLESHOOTING 2.6.1 Choosing a representation 2.6.2 Loading and creating graphs 2.7 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Structure of networks 3.1 NETWORK PARAMETERS 3.1.1 Fundamental parameters 3.1.2 Measures of centrality 3.1.3 Mixing patterns: assortativity 3.2 CANONICAL NETWORK MODELS 3.2.1 Erdos–Rényi (ER) network model 3.2.2 Small-world networks 3.2.3 Scale-free networks 3.2.4 Other models of network generation 3.3 COMMUNITY DETECTION 3.3.1 Modularity maximisation 3.3.2 Similarity-based clustering 3.3.3 Girvan–Newman algorithm 3.3.4 Other methods 3.3.5 Community detection in biological networks 3.4 NETWORKMOTIFS 3.4.1 Randomising networks 3.5 PERTURBATIONS TO NETWORKS 3.5.1 Quantifying e□fects of perturbation 3.5.2 Network structure and attack strategies 3.6 TROUBLESHOOTING 3.6.1 Is your network really scale-free? 3.7 SOFTWARE TOOLS EXERCISES REFERENCESFURTHER READING Applications of network biology 4.1 THE CENTRALITY–LETHALITY HYPOTHESIS 4.1.1 Predicting essential genes fromnetworks 4.2 NETWORKS AND MODULES IN DISEASE 4.2.1 Disease networks 4.2.2 Identification of disease modules 4.2.3 Edgetic perturbation models 4.3 DIFFERENTIAL NETWORK ANALYSIS 4.4 DISEASE SPREADING ON NETWORKS 4.4.1 Percolation-based models 4.4.2 Agent-based simulations 4.5 MOLECULAR GRAPHS AND THEIR APPLICATIONS 4.5.1 Retrosynthesis 4.6 PROTEIN STRUCTURE, ENERGY & CONFORMATIONAL NETWORKS4.6.1 Protein folding pathways 4.7 LINK PREDICTION EXERCISES REFERENCES FURTHER READING Introduction to dynamic modelling5.1 CONSTRUCTING DYNAMIC MODELS 5.1.1 Modelling a generic biochemical system 5.2 MASS-ACTION KINETIC MODELS 5.3 MODELLING ENZYME KINETICS 5.3.1 The Michaelis–Menten model 5.3.2 Extending the Michaelis–Menten model 5.3.3 Limitations of Michaelis–Menten models 5.3.4 Co-operativity: Hill kinetics 5.3.5 An illustrative example: a three-node oscillator 5.4 GENERALISED RATE EQUATIONS 5.4.1 Biochemical systems theory 5.5 SOLVING ODES 5.6 TROUBLESHOOTING 5.6.1 Handing sti□f equations 5.6.2 Handling uncertainty 5.7 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Parameter estimation 6.1 DATA-DRIVEN MECHANISTIC MODELLING: AN OVERVIEW 6.1.1 Pre-processing the data 6.1.2 Model identification 6.2 SETTING UP AN OPTIMISATION PROBLEM 6.2.1 Linear regression 6.2.2 Least squares 6.2.3 Maximumlikelihood estimation 6.3 ALGORITHMS FOR OPTIMISATION 6.3.1 Desiderata 6.3.2 Gradient-based methods 6.3.3 Direct search methods 6.3.4 Evolutionary algorithms 6.4 POST-REGRESSION DIAGNOSTICS 6.4.1 Model selection 6.4.2 Sensitivity and robustness of biological models 6.5 TROUBLESHOOTING 6.5.1 Regularisation 6.5.2 Sloppiness 6.5.3 Choosing a search algorithm 6.5.4 Model reduction 6.5.5 The curse of dimensionality 6.6 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Discrete dynamic models: Boolean networks 7.1 INTRODUCTION 7.2 BOOLEAN NETWORKS: TRANSFER FUNCTIONS 7.2.1 Characterising Boolean network dynamics 7.2.2 Synchronous vs. asynchronous updates 7.3 OTHER PARADIGMS 7.3.1 Probabilistic Boolean networks 7.3.2 Logical interaction hypergraphs 7.3.3 Generalised logical networks 7.3.4 Petri nets 7.4 APPLICATIONS 7.5 TROUBLESHOOTING 7.6 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Introduction to constraint-based modelling 8.1 WHAT ARE CONSTRAINTS? 8.1.1 Types of constraints 8.1.2 Mathematical representation of constraints 8.1.3 Why are constraints useful? 8.2 THE STOICHIOMETRICMATRIX 8.3 STEADY-STATEMASSBALANCE:FLUXBALANCEANALYSIS (FBA)8.4 THE OBJECTIVE FUNCTION 8.4.1 The biomass objective function 8.5 OPTIMISATION TO COMPUTE FLUX DISTRIBUTION 8.6 AN ILLUSTRATION 8.7 FLUX VARIABILITY ANALYSIS (FVA) 8.8 UNDERSTANDING FBA 8.8.1 Blocked reactions and dead-end metabolites 8.8.2 Gaps in metabolic networks 8.8.3 Multiple solutions8.8.4 Loops 8.8.5 Parsimonious FBA (pFBA) 8.8.6 ATP maintenance fluxes 8.9 TROUBLESHOOTING 8.9.1 Zero growth rate 8.9.2 Objective values vs. flux values 8.10 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Extending constraint-based approaches 9.1 MINIMISATION OF METABOLIC ADJUSTMENT (MOMA) 9.1.1 Fitting experimentally measured fluxes 9.2 REGULATORY ON-OFF MINIMISATION (ROOM) 9.2.1 ROOMvs.MoMA 9.3 BI-LEVEL OPTIMISATIONS 9.3.1 OptKnock9.4 INTEGRATING REGULATORY INFORMATION 9.4.1 Embedding regulatory logic: regulatory FBA (rFBA) 9.4.2 Informing metabolic models with omic data 9.4.3 Tissue-specific models 9.5 COMPARTMENTALISED MODELS 9.6 DYNAMIC FLUX BALANCE ANALYSIS (dFBA) 9.7 13C-MFA 9.8 ELEMENTARY FLUX MODES AND EXTREME PATHWAYS 9.8.1 Computing EFMs and EPs 9.8.2 Applications EXERCISES REFERENCES FURTHER READING Perturbations to metabolic networks10.1 KNOCK-OUTS 10.1.1 Gene deletions vs. reaction deletions 10.2 SYNTHETIC LETHALS 10.2.1 Exhaustive enumeration 10.2.2 Bi-level optimisation 10.2.3 Fast-SL: massively pruning the search space 10.3 OVER-EXPRESSION 10.3.1 Flux Scanning based on Enforced Objective Flux (FSEOF) 10.4 OTHER PERTURBATIONS 10.5 EVALUATING AND RANKING PERTURBATIONS 10.6 APPLICATIONS OF CONSTRAINT-BASED MODELS 10.6.1 Metabolic engineering 10.6.2 Drug target identification 10.7 LIMITATIONS OF CONSTRAINT-BASED APPROACHES 10.7.1 Scope of genome-scale metabolic models 10.7.2 Incorrect predictions 10.8 TROUBLESHOOTING10.8.1 Interpreting gene deletion simulations 10.9 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Modelling cellular interactions 11.1 MICROBIAL COMMUNITIES 11.1.1 Network-based approaches 11.1.2 Population-based and agent-based approaches 11.1.3 Constraint-based approaches 11.2 HOST–PATHOGEN INTERACTIONS (HPIs) 11.2.1 Network models 11.2.2 Dynamic models 11.2.3 Constraint-based models 11.3 SUMMARY11.4 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Designing biological circuits 12.1 WHAT IS SYNTHETIC BIOLOGY? 12.2 FROMLEGO BRICKS TO BIOBRICKS 12.3 CLASSIC CIRCUIT DESIGN EXPERIMENTS 12.3.1 Designing an oscillator: the repressilator 12.3.2 Toggle switch 12.4 DESIGNING MODULES 12.4.1 Exploring the design space 12.4.2 Systems-theoretic approaches 12.4.3 Automating circuit design 12.5 DESIGN PRINCIPLES OF BIOLOGICAL NETWORKS 12.5.1 Redundancy 12.5.2 Modularity 12.5.3 Exaptation 12.5.4 Robustness 12.6 COMPUTING WITH CELLS 12.6.1 Adleman’s classic experiment 12.6.2 Examples of circuits that can compute 12.6.3 DNA data storage 12.7 CHALLENGES 12.8 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Robustness and evolvability of biological systems 13.1 ROBUSTNESS IN BIOLOGICAL SYSTEMS 13.1.1 Key mechanisms 13.1.2 Hierarchies and protocols 13.1.3 Organising principles 13.2 GENOTYPE SPACES AND GENOTYPE NETWORKS 13.2.1 Genotype spaces 13.2.2 Genotype–phenotype mapping 13.3 QUANTIFYING ROBUSTNESS AND EVOLVABILITY 13.4 SOFTWARE TOOLS EXERCISES REFERENCES FURTHER READING Epilogue: The Road Ahead Index 325
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Taylor & Francis Ltd Thermodynamics in Bioenergetics
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Taylor & Francis Ltd Biomembrane Simulations Computational Studies of Biological Membranes
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Taylor & Francis Ltd Computational Biology
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