Computational Physiology
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Computational Physiology
Author: Kimberly J. McCabe
language: en
Publisher: Springer Nature
Release Date: 2023-03-01
This open access volume compiles student reports from the 2022 Simula Summer School in Computational Physiology. The reports provide an overview of some tools available to model physiology in excitable tissues across scales and scientific questions. In 2022, Simula held the eighth annual Summer School in Computational Physiology in collaboration with the University of Oslo (UiO) and the University of California, San Diego (UCSD). Each year, the course focuses on modeling excitable tissues, with a special interest in cardiac physiology and neuroscience. Group research projects conducted by graduate students from around the world result in reports addressing problems of physiological importance. Reports may not necessarily represent new scientific results; rather, they can reproduce or supplement earlier studies. Reports from seven of the summer projects are included as separate chapters. The topics represented include multiscale mechanics, electrophysiology, pharmacology, and machine learning.
Mathematical Modeling and Validation in Physiology
This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data. Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited.
Quantitative Physiology
Stephen Hawking says that the 21st century will be the century of complexity and indeed now systems biology or medicine means dealing with complexity. Both the genome and physiome have emerged in studying complex physiological systems. Computational and mathematical modeling has been regarded as an efficient tool to boost the understanding about living systems in normal or pathophysiological states. Covering applied methodology, basic case studies and complex applications, this volume provides researchers with an overview of modeling and computational studies of physiology (i.e. quantitative physiology), which is becoming an increasingly important branch of systems biology. This book aims to build multi-scale models to investigate functions in living systems and explain how biomolecules, cells, organs, organ systems and organisms carry out the chemical or physical functions. Some of the models addressed are related to gene expression, calcium signalling, neural activity, blood dynamics and bone mechanics. Combining theory and practice, with extensive use of MATLAB, this book is designed to establish a paradigm for quantitative physiology by integrating biology, mathematics, physics and informatics etc. To benefit from this book, the readers are expected to have a background in general physiology and mathematics