Coverart for item
The Resource Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis

Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis

Label
Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches
Title
Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics
Title remainder
homogeneous and heterogeneous approaches
Statement of responsibility
Panos Macheras, Athanassios Iliadis
Creator
Contributor
Subject
Language
eng
Member of
Cataloging source
MMU
http://library.link/vocab/creatorName
Macheras, P.
Dewey number
615/.7
Illustrations
illustrations
Index
index present
LC call number
RM301.5
LC item number
.M33 2006
Literary form
non fiction
Nature of contents
bibliography
NLM call number
  • 2006 C-872
  • QV 38
NLM item number
M149m 2006
http://library.link/vocab/relatedWorkOrContributorName
Iliadis, Athanassios
Series statement
Interdisciplinary applied mathematics
Series volume
v. 30
http://library.link/vocab/subjectName
  • Biopharmaceutics
  • Pharmacokinetics
  • Drugs
  • Biopharmaceutics
  • Models, Theoretical
  • Pharmacokinetics
  • Biopharmacie
  • Pharmacocinétique
  • Médicaments
  • Biopharmacie
  • Pharmacocinétique
  • Pharmacodynamie
  • Biomathematik
  • Biopharmazie
  • Pharmakodynamik
  • Pharmakokinetik
  • Pharmacodynamie - Modèles mathématiques
Label
Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis
Instantiates
Publication
Bibliography note
Includes bibliographical references (pages 383-432) and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 8
  • 51
  • II
  • Modeling in Biopharmaceutics
  • 53
  • 4
  • Drug Release
  • 57
  • 4.1
  • The Higuchi Model
  • 58
  • 1.3
  • 4.2
  • Systems with Different Geometries
  • 60
  • 4.3
  • The Power-Law Model
  • 63
  • 4.3.1
  • Higuchi Model vs. Power-Law Model
  • 64
  • 4.4
  • Fractal Dimension
  • Recent Mechanistic Models
  • 67
  • 4.5
  • Monte Carlo Simulations
  • 68
  • 4.5.1
  • Verification of the Higuchi Law
  • 69
  • 4.5.2
  • Drug Release from Homogeneous Cylinders
  • 9
  • 70
  • 4.5.3
  • Release from Fractal Matrices
  • 75
  • 4.6
  • Discernment of Drug Release Kinetics
  • 82
  • 4.7
  • Release from Bioerodible Microparticles
  • 83
  • 1.4
  • 4.8
  • Dynamic Aspects in Drug Release
  • 86
  • 5
  • Drug Dissolution
  • 89
  • 5.1
  • The Diffusion Layer Model
  • 90
  • 5.1.1
  • Estimation of Fractal Dimension
  • Alternative Classical Dissolution Relationships
  • 92
  • 5.1.2
  • Fractal Considerations in Drug Dissolution
  • 93
  • 5.1.3
  • On the Use of the Weibull Function in Dissolution
  • 94
  • 5.1.4
  • Stochastic Considerations
  • 11
  • 97
  • 5.2
  • The Interfacial Barrier Model
  • 100
  • 5.2.1
  • A Continuous Reaction-Limited Dissolution Model
  • 100
  • 5.2.2
  • A Discrete Reaction-Limited Dissolution Model
  • 101
  • 1.4.1
  • 5.2.3
  • Modeling Supersaturated Dissolution Data
  • 107
  • 5.3
  • Modeling Random Effects
  • 109
  • 5.4
  • Homogeneity vs. Heterogeneity
  • 110
  • 5.5
  • Self-Similarity Considerations
  • Comparison of Dissolution Profiles
  • 111
  • 6
  • Oral Drug Absorption
  • 113
  • 6.1
  • Pseudoequilibrium Models
  • 114
  • 6.1.1
  • The pH-Partition Hypothesis
  • 11
  • 114
  • 6.1.2
  • Absorption Potential
  • 115
  • 6.2
  • Mass Balance Approaches
  • 117
  • 6.2.1
  • Macroscopic Approach
  • 118
  • 1
  • 1.4.2
  • 6.2.2
  • Microscopic Approach
  • 121
  • 6.3
  • Dynamic Models
  • 122
  • 6.3.1
  • Compartmental Models
  • 122
  • 6.3.2
  • Power-Law Scaling
  • Convection-Dispersion Models
  • 124
  • 6.4
  • Heterogeneous Approaches
  • 129
  • 6.4.1
  • The Heterogeneous Character of GI Transit
  • 129
  • 6.4.2
  • Is in Vivo Drug Dissolution a Fractal Process?
  • 12
  • 130
  • 6.4.3
  • Fractal-like Kinetics in Gastrointestinal Absorption
  • 132
  • 6.4.4
  • The Fractal Nature of Absorption Processes
  • 134
  • 6.4.5
  • Modeling Drug Transit in the Intestines
  • 136
  • 1.5
  • 6.4.6
  • Probabilistic Model for Drug Absorption
  • 142
  • 6.5
  • Absorption Models Based on Structure
  • 147
  • 6.6
  • Regulatory Aspects
  • 148
  • 6.6.1
  • Self-Affine Fractals
  • Biopharmaceutics Classification of Drugs
  • 148
  • 6.6.2
  • The Problem with the Biowaivers
  • 151
  • 6.7
  • Randomness and Chaotic Behavior
  • 158
  • III
  • Modeling In Pharmacokinetics
  • 12
  • 161
  • 7
  • Empirical Models
  • 165
  • 7.1
  • Power Functions and Heterogeneity
  • 167
  • 7.2
  • Heterogeneous Processes
  • 169
  • 1.6
  • 7.2.1
  • Distribution, Blood Vessels Network
  • 169
  • 7.2.2
  • Elimination, Liver Structure
  • 171
  • 7.3
  • Fractal Time and Fractal Processes
  • 174
  • 7.4
  • More About Dimensionality
  • Modeling Heterogeneity
  • 175
  • 7.4.1
  • Fractal Concepts
  • 176
  • 7.4.2
  • Empirical Concepts
  • 177
  • 7.5
  • Heterogeneity and Time Dependence
  • 13
  • 178
  • 7.6
  • Simulation with Empirical Models
  • 181
  • 8
  • Deterministic Compartmental Models
  • 183
  • 8.1
  • Linear Compartmental Models
  • 184
  • 1.7
  • 8.2
  • Routes of Administration
  • 186
  • 8.3
  • Time-Concentration Profiles
  • 187
  • 8.4
  • Random Fractional Flow Rates
  • 188
  • 8.5
  • The Geometry of Nature
  • Percolation
  • Nonlinear Compartmental Models
  • 189
  • 8.5.1
  • The Enzymatic Reaction
  • 191
  • 8.6
  • Complex Deterministic Models
  • 193
  • 8.6.1
  • Geometric Considerations
  • 14
  • 194
  • 8.6.2
  • Tracer Washout Curve
  • 195
  • 8.6.3
  • Model for the Circulatory System
  • 197
  • 8.7
  • Compartmental Models and Heterogeneity
  • 199
  • 2
  • 9
  • Stochastic Compartmental Models
  • 205
  • 9.1
  • Probabilistic Transfer Models
  • 206
  • 9.1.2
  • The Basic Steps
  • 208
  • 9.2
  • Diffusion and Kinetics
  • Retention-Time Distribution Models
  • 210
  • 9.2.1
  • Probabilistic vs. Retention-Time Models
  • 210
  • 9.2.2
  • Markov vs. Semi-Markov Models
  • 212
  • 9.2.3
  • Irreversible Models
  • 17
  • 214
  • 9.2.4
  • Reversible Models
  • 217
  • 9.2.5
  • Time-Varying Hazard Rates
  • 222
  • 9.2.6
  • Pseudocompartment Techniques
  • 225
  • 2.1
  • 9.2.7
  • A Typical Two-Compartment Model
  • 231
  • 9.3
  • Time-Concentration Profiles
  • 235
  • 9.3.1
  • Routes of Administration
  • 236
  • 9.3.2
  • Random Walks and Regular Diffusion
  • Some Typical Drug Administration Schemes
  • 237
  • 9.3.3
  • Time-Amount Functions
  • 239
  • 9.3.4
  • Process Uncertainty or Stochastic Error
  • 243
  • 9.3.5
  • Distribution of Particles and Process Uncertainty
  • 18
  • 245
  • 9.3.6
  • Time Profiles of the Model
  • 249
  • 9.4
  • Random Hazard-Rate Models
  • 251
  • 9.4.1
  • Probabilistic Models with Random Hazard Rates
  • 253
  • 2.2
  • 9.4.2
  • Retention-Time Models with Random Hazard Rates
  • 258
  • 9.5
  • The Kolmogorov or Master Equations
  • 260
  • 9.5.1
  • Master Equation and Diffusion
  • 263
  • 9.5.2
  • Anomalous Diffusion
  • Exact Solution in Matrix Form
  • 265
  • 9.5.3
  • Cumulant Generating Functions
  • 265
  • 9.5.4
  • Stochastic Simulation Algorithm
  • 267
  • 9.5.5
  • Simulation of Linear and Nonlinear Models
  • 5
  • 22
  • 272
  • 9.6
  • Fractals and Stochastic Modeling
  • 281
  • 9.7
  • Stochastic vs. Deterministic Models
  • 285
  • IV
  • Modeling in Pharmacodynamics
  • 289
  • 2.3
  • 10
  • Classical Pharmacodynamics
  • 293
  • 10.1
  • Occupancy Theory in Pharmacology
  • 293
  • 10.2
  • Empirical Pharmacodynamic Models
  • 295
  • 10.3
  • Fick's Laws of Diffusion
  • Pharmacokinetic-Dynamic Modeling
  • 296
  • 10.3.1
  • Link Models
  • 297
  • 10.3.2
  • Response Models
  • 303
  • 10.4
  • Other Pharmacodynamic Models
  • 23
  • 305
  • 10.4.1
  • The Receptor-Transducer Model
  • 305
  • 10.4.2
  • Irreversible Models
  • 305
  • 10.4.3
  • Time-Variant Models
  • 306
  • 2.4
  • 10.4.4
  • Dynamic Nonlinear Models
  • 308
  • 10.5
  • Unification of Pharmacodynamic Models
  • 309
  • 10.6
  • The Population Approach
  • 310
  • 10.6.1
  • Classical Kinetics
  • Inter- and Intraindividual Variability
  • 310
  • 10.6.2
  • Models and Software
  • 311
  • 10.6.3
  • Covariates
  • 312
  • 10.6.4
  • Applications
  • 27
  • 313
  • 11
  • Nonclassical Pharmacodynamics
  • 315
  • 11.1
  • Nonlinear Concepts in Pharmacodynamics
  • 316
  • 11.1.1
  • Negative Feedback
  • 316
  • 2.4.1
  • 11.1.2
  • Delayed Negative Feedback
  • 322
  • 11.2
  • Pharmacodynamic Applications
  • 334
  • 11.2.1
  • Drugs Affecting Endocrine Function
  • 334
  • 11.2.2
  • Passive Transport Processes
  • Central Nervous System Drugs
  • 344
  • 11.2.3
  • Cardiovascular Drugs
  • 348
  • A Stability Analysis
  • 353
  • B
  • Monte Carlo Simulations in Drug Release
  • 355
  • 28
  • C
  • Time-Varying Models
  • 359
  • D
  • Probability
  • 363
  • D.1
  • Basic Properties
  • 363
  • D.2
  • 1.1
  • 2.4.2
  • Expectation, Variance, and Covariance
  • 364
  • D.3
  • Conditional Expectation and Variance
  • 365
  • D.4
  • Generating Functions
  • 365
  • E
  • Convolution in Probability Theory
  • Reaction Processes: Diffusion- or Reaction-Limited?
  • 367
  • F
  • Laplace Transform
  • 369
  • G
  • Estimation
  • 371
  • H
  • Theorem on Continuous Functions
  • 373
  • 29
  • 2.4.3
  • Carrier-Mediated Transport
  • 30
  • 2.5
  • Fractal-like Kinetics
  • 31
  • 2.5.1
  • Geometric and Statistical Self-Similarity
  • Segregation of Reactants
  • 31
  • 2.5.2
  • Time-Dependent Rate Coefficients
  • 32
  • 2.5.3
  • Effective Rate Equations
  • 34
  • 2.5.4
  • Enzyme-Catalyzed Reactions
  • 6
  • 35
  • 2.5.5
  • Importance of the Power-Law Expressions
  • 36
  • 2.6
  • Fractional Diffusion Equations
  • 36
  • 3
  • Nonlinear Dynamics
  • 39
  • 1.2
  • 3.1
  • Dynamic Systems
  • 41
  • 3.2
  • Attractors
  • 42
  • 3.3
  • Bifurcation
  • 43
  • 3.4
  • Scaling
  • Sensitivity to Initial Conditions
  • 45
  • 3.5
  • Reconstruction of the Phase Space
  • 47
  • 3.6
  • Estimation and Control in Chaotic Systems
  • 49
  • 3.7
  • Physiological Systems
Control code
63188951
Dimensions
25 cm
Extent
xx, 442 pages
Isbn
9780387281780
Lccn
2005934524
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other control number
9780387281780
Other physical details
illustrations
System control number
(OCoLC)63188951
Label
Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis
Publication
Bibliography note
Includes bibliographical references (pages 383-432) and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 8
  • 51
  • II
  • Modeling in Biopharmaceutics
  • 53
  • 4
  • Drug Release
  • 57
  • 4.1
  • The Higuchi Model
  • 58
  • 1.3
  • 4.2
  • Systems with Different Geometries
  • 60
  • 4.3
  • The Power-Law Model
  • 63
  • 4.3.1
  • Higuchi Model vs. Power-Law Model
  • 64
  • 4.4
  • Fractal Dimension
  • Recent Mechanistic Models
  • 67
  • 4.5
  • Monte Carlo Simulations
  • 68
  • 4.5.1
  • Verification of the Higuchi Law
  • 69
  • 4.5.2
  • Drug Release from Homogeneous Cylinders
  • 9
  • 70
  • 4.5.3
  • Release from Fractal Matrices
  • 75
  • 4.6
  • Discernment of Drug Release Kinetics
  • 82
  • 4.7
  • Release from Bioerodible Microparticles
  • 83
  • 1.4
  • 4.8
  • Dynamic Aspects in Drug Release
  • 86
  • 5
  • Drug Dissolution
  • 89
  • 5.1
  • The Diffusion Layer Model
  • 90
  • 5.1.1
  • Estimation of Fractal Dimension
  • Alternative Classical Dissolution Relationships
  • 92
  • 5.1.2
  • Fractal Considerations in Drug Dissolution
  • 93
  • 5.1.3
  • On the Use of the Weibull Function in Dissolution
  • 94
  • 5.1.4
  • Stochastic Considerations
  • 11
  • 97
  • 5.2
  • The Interfacial Barrier Model
  • 100
  • 5.2.1
  • A Continuous Reaction-Limited Dissolution Model
  • 100
  • 5.2.2
  • A Discrete Reaction-Limited Dissolution Model
  • 101
  • 1.4.1
  • 5.2.3
  • Modeling Supersaturated Dissolution Data
  • 107
  • 5.3
  • Modeling Random Effects
  • 109
  • 5.4
  • Homogeneity vs. Heterogeneity
  • 110
  • 5.5
  • Self-Similarity Considerations
  • Comparison of Dissolution Profiles
  • 111
  • 6
  • Oral Drug Absorption
  • 113
  • 6.1
  • Pseudoequilibrium Models
  • 114
  • 6.1.1
  • The pH-Partition Hypothesis
  • 11
  • 114
  • 6.1.2
  • Absorption Potential
  • 115
  • 6.2
  • Mass Balance Approaches
  • 117
  • 6.2.1
  • Macroscopic Approach
  • 118
  • 1
  • 1.4.2
  • 6.2.2
  • Microscopic Approach
  • 121
  • 6.3
  • Dynamic Models
  • 122
  • 6.3.1
  • Compartmental Models
  • 122
  • 6.3.2
  • Power-Law Scaling
  • Convection-Dispersion Models
  • 124
  • 6.4
  • Heterogeneous Approaches
  • 129
  • 6.4.1
  • The Heterogeneous Character of GI Transit
  • 129
  • 6.4.2
  • Is in Vivo Drug Dissolution a Fractal Process?
  • 12
  • 130
  • 6.4.3
  • Fractal-like Kinetics in Gastrointestinal Absorption
  • 132
  • 6.4.4
  • The Fractal Nature of Absorption Processes
  • 134
  • 6.4.5
  • Modeling Drug Transit in the Intestines
  • 136
  • 1.5
  • 6.4.6
  • Probabilistic Model for Drug Absorption
  • 142
  • 6.5
  • Absorption Models Based on Structure
  • 147
  • 6.6
  • Regulatory Aspects
  • 148
  • 6.6.1
  • Self-Affine Fractals
  • Biopharmaceutics Classification of Drugs
  • 148
  • 6.6.2
  • The Problem with the Biowaivers
  • 151
  • 6.7
  • Randomness and Chaotic Behavior
  • 158
  • III
  • Modeling In Pharmacokinetics
  • 12
  • 161
  • 7
  • Empirical Models
  • 165
  • 7.1
  • Power Functions and Heterogeneity
  • 167
  • 7.2
  • Heterogeneous Processes
  • 169
  • 1.6
  • 7.2.1
  • Distribution, Blood Vessels Network
  • 169
  • 7.2.2
  • Elimination, Liver Structure
  • 171
  • 7.3
  • Fractal Time and Fractal Processes
  • 174
  • 7.4
  • More About Dimensionality
  • Modeling Heterogeneity
  • 175
  • 7.4.1
  • Fractal Concepts
  • 176
  • 7.4.2
  • Empirical Concepts
  • 177
  • 7.5
  • Heterogeneity and Time Dependence
  • 13
  • 178
  • 7.6
  • Simulation with Empirical Models
  • 181
  • 8
  • Deterministic Compartmental Models
  • 183
  • 8.1
  • Linear Compartmental Models
  • 184
  • 1.7
  • 8.2
  • Routes of Administration
  • 186
  • 8.3
  • Time-Concentration Profiles
  • 187
  • 8.4
  • Random Fractional Flow Rates
  • 188
  • 8.5
  • The Geometry of Nature
  • Percolation
  • Nonlinear Compartmental Models
  • 189
  • 8.5.1
  • The Enzymatic Reaction
  • 191
  • 8.6
  • Complex Deterministic Models
  • 193
  • 8.6.1
  • Geometric Considerations
  • 14
  • 194
  • 8.6.2
  • Tracer Washout Curve
  • 195
  • 8.6.3
  • Model for the Circulatory System
  • 197
  • 8.7
  • Compartmental Models and Heterogeneity
  • 199
  • 2
  • 9
  • Stochastic Compartmental Models
  • 205
  • 9.1
  • Probabilistic Transfer Models
  • 206
  • 9.1.2
  • The Basic Steps
  • 208
  • 9.2
  • Diffusion and Kinetics
  • Retention-Time Distribution Models
  • 210
  • 9.2.1
  • Probabilistic vs. Retention-Time Models
  • 210
  • 9.2.2
  • Markov vs. Semi-Markov Models
  • 212
  • 9.2.3
  • Irreversible Models
  • 17
  • 214
  • 9.2.4
  • Reversible Models
  • 217
  • 9.2.5
  • Time-Varying Hazard Rates
  • 222
  • 9.2.6
  • Pseudocompartment Techniques
  • 225
  • 2.1
  • 9.2.7
  • A Typical Two-Compartment Model
  • 231
  • 9.3
  • Time-Concentration Profiles
  • 235
  • 9.3.1
  • Routes of Administration
  • 236
  • 9.3.2
  • Random Walks and Regular Diffusion
  • Some Typical Drug Administration Schemes
  • 237
  • 9.3.3
  • Time-Amount Functions
  • 239
  • 9.3.4
  • Process Uncertainty or Stochastic Error
  • 243
  • 9.3.5
  • Distribution of Particles and Process Uncertainty
  • 18
  • 245
  • 9.3.6
  • Time Profiles of the Model
  • 249
  • 9.4
  • Random Hazard-Rate Models
  • 251
  • 9.4.1
  • Probabilistic Models with Random Hazard Rates
  • 253
  • 2.2
  • 9.4.2
  • Retention-Time Models with Random Hazard Rates
  • 258
  • 9.5
  • The Kolmogorov or Master Equations
  • 260
  • 9.5.1
  • Master Equation and Diffusion
  • 263
  • 9.5.2
  • Anomalous Diffusion
  • Exact Solution in Matrix Form
  • 265
  • 9.5.3
  • Cumulant Generating Functions
  • 265
  • 9.5.4
  • Stochastic Simulation Algorithm
  • 267
  • 9.5.5
  • Simulation of Linear and Nonlinear Models
  • 5
  • 22
  • 272
  • 9.6
  • Fractals and Stochastic Modeling
  • 281
  • 9.7
  • Stochastic vs. Deterministic Models
  • 285
  • IV
  • Modeling in Pharmacodynamics
  • 289
  • 2.3
  • 10
  • Classical Pharmacodynamics
  • 293
  • 10.1
  • Occupancy Theory in Pharmacology
  • 293
  • 10.2
  • Empirical Pharmacodynamic Models
  • 295
  • 10.3
  • Fick's Laws of Diffusion
  • Pharmacokinetic-Dynamic Modeling
  • 296
  • 10.3.1
  • Link Models
  • 297
  • 10.3.2
  • Response Models
  • 303
  • 10.4
  • Other Pharmacodynamic Models
  • 23
  • 305
  • 10.4.1
  • The Receptor-Transducer Model
  • 305
  • 10.4.2
  • Irreversible Models
  • 305
  • 10.4.3
  • Time-Variant Models
  • 306
  • 2.4
  • 10.4.4
  • Dynamic Nonlinear Models
  • 308
  • 10.5
  • Unification of Pharmacodynamic Models
  • 309
  • 10.6
  • The Population Approach
  • 310
  • 10.6.1
  • Classical Kinetics
  • Inter- and Intraindividual Variability
  • 310
  • 10.6.2
  • Models and Software
  • 311
  • 10.6.3
  • Covariates
  • 312
  • 10.6.4
  • Applications
  • 27
  • 313
  • 11
  • Nonclassical Pharmacodynamics
  • 315
  • 11.1
  • Nonlinear Concepts in Pharmacodynamics
  • 316
  • 11.1.1
  • Negative Feedback
  • 316
  • 2.4.1
  • 11.1.2
  • Delayed Negative Feedback
  • 322
  • 11.2
  • Pharmacodynamic Applications
  • 334
  • 11.2.1
  • Drugs Affecting Endocrine Function
  • 334
  • 11.2.2
  • Passive Transport Processes
  • Central Nervous System Drugs
  • 344
  • 11.2.3
  • Cardiovascular Drugs
  • 348
  • A Stability Analysis
  • 353
  • B
  • Monte Carlo Simulations in Drug Release
  • 355
  • 28
  • C
  • Time-Varying Models
  • 359
  • D
  • Probability
  • 363
  • D.1
  • Basic Properties
  • 363
  • D.2
  • 1.1
  • 2.4.2
  • Expectation, Variance, and Covariance
  • 364
  • D.3
  • Conditional Expectation and Variance
  • 365
  • D.4
  • Generating Functions
  • 365
  • E
  • Convolution in Probability Theory
  • Reaction Processes: Diffusion- or Reaction-Limited?
  • 367
  • F
  • Laplace Transform
  • 369
  • G
  • Estimation
  • 371
  • H
  • Theorem on Continuous Functions
  • 373
  • 29
  • 2.4.3
  • Carrier-Mediated Transport
  • 30
  • 2.5
  • Fractal-like Kinetics
  • 31
  • 2.5.1
  • Geometric and Statistical Self-Similarity
  • Segregation of Reactants
  • 31
  • 2.5.2
  • Time-Dependent Rate Coefficients
  • 32
  • 2.5.3
  • Effective Rate Equations
  • 34
  • 2.5.4
  • Enzyme-Catalyzed Reactions
  • 6
  • 35
  • 2.5.5
  • Importance of the Power-Law Expressions
  • 36
  • 2.6
  • Fractional Diffusion Equations
  • 36
  • 3
  • Nonlinear Dynamics
  • 39
  • 1.2
  • 3.1
  • Dynamic Systems
  • 41
  • 3.2
  • Attractors
  • 42
  • 3.3
  • Bifurcation
  • 43
  • 3.4
  • Scaling
  • Sensitivity to Initial Conditions
  • 45
  • 3.5
  • Reconstruction of the Phase Space
  • 47
  • 3.6
  • Estimation and Control in Chaotic Systems
  • 49
  • 3.7
  • Physiological Systems
Control code
63188951
Dimensions
25 cm
Extent
xx, 442 pages
Isbn
9780387281780
Lccn
2005934524
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other control number
9780387281780
Other physical details
illustrations
System control number
(OCoLC)63188951

Library Locations

    • J. Otto Lottes Health Sciences LibraryBorrow it
      1 Hospital Dr, Columbia, MO, 65201, US
      38.939544 -92.328377
Processing Feedback ...