Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine. The second edition, which is completely updated and expanded, opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration.
The focus of Modelling Methodology for Physiology and Medicine, Second Edition, is the methodology that underpins good modeling practice. It builds upon the idea of an integrated methodology for the development and testing of mathematical models. It covers many specific areas of methodology in which important advances have taken place over recent years and illustrates the application of good methodological practice in key areas of physiology and medicine. It builds on work that the editors have carried out over the past 30 years, working in cooperation with leading practitioners in the field.
1. 1. An Introduction to Modelling Methodology - p. XIX 2. 2. Control in Physiology and Medicine - p. 11 3. 3. Deconvolution - p. 40 4. 4. Structural Identifiability of Biological and Physiological Systems - p. 66 5. 5. Parameter Estimation - p. 81 6. 6. New Trends in Nonparametric Linear System Identification - p. 109 7. 7. Population Modelling - p. 127 8. 8. Systems Biology - p. 156 9. 9. Reverse Engineering of High-Throughput Genomic and Genetic Data - p. 183 10. 10. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State - p. 202 11. 11. Stochastic Models of Physiology - p. 229 12. 12. Probabilistic Modelling with Bayesian Networks - p. 253 13. 13. Mathematical Modelling of Pulmonary Gas Exchange - p. 276 14. 14. Mathematical Models for Computational Neuroscience - p. 309 15. 15. Insulin Modelling - p. 331 16. 16. Glucose Modelling - p. 349 17. 17. Blood–Tissue Exchange Modelling - p. 377 18. 18. Physiological Modelling of Positron Emission Tomography Images - p. 410 19. 19. Tumor Growth Modelling for Drug Development - p. 444 20. 20. Computational Modelling of Cardiac Biomechanics - p. 476 21. 21. Downstream from the Heart Left Ventricle: Aortic Impedance Interpretation by Lumped and Tube-Load Models - p. 499 22. 22. Finite Element Modelling in Musculoskeletal Biomechanics - p. 522 23. 23. Modelling for Synthetic Biology - p. 540
Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine. The second edition, which is completely updated and expanded, opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration.
The focus of Modelling Methodology for Physiology and Medicine, Second Edition, is the methodology that underpins good modeling practice. It builds upon the idea of an integrated methodology for the development and testing of mathematical models. It covers many specific areas of methodology in which important advances have taken place over recent years and illustrates the application of good methodological practice in key areas of physiology and medicine. It builds on work that the editors have carried out over the past 30 years, working in cooperation with leading practitioners in the field.
1. 1. An Introduction to Modelling Methodology - p. XIX 2. 2. Control in Physiology and Medicine - p. 11 3. 3. Deconvolution - p. 40 4. 4. Structural Identifiability of Biological and Physiological Systems - p. 66 5. 5. Parameter Estimation - p. 81 6. 6. New Trends in Nonparametric Linear System Identification - p. 109 7. 7. Population Modelling - p. 127 8. 8. Systems Biology - p. 156 9. 9. Reverse Engineering of High-Throughput Genomic and Genetic Data - p. 183 10. 10. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State - p. 202 11. 11. Stochastic Models of Physiology - p. 229 12. 12. Probabilistic Modelling with Bayesian Networks - p. 253 13. 13. Mathematical Modelling of Pulmonary Gas Exchange - p. 276 14. 14. Mathematical Models for Computational Neuroscience - p. 309 15. 15. Insulin Modelling - p. 331 16. 16. Glucose Modelling - p. 349 17. 17. Blood–Tissue Exchange Modelling - p. 377 18. 18. Physiological Modelling of Positron Emission Tomography Images - p. 410 19. 19. Tumor Growth Modelling for Drug Development - p. 444 20. 20. Computational Modelling of Cardiac Biomechanics - p. 476 21. 21. Downstream from the Heart Left Ventricle: Aortic Impedance Interpretation by Lumped and Tube-Load Models - p. 499 22. 22. Finite Element Modelling in Musculoskeletal Biomechanics - p. 522 23. 23. Modelling for Synthetic Biology - p. 540
