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定量生理学(Quantitative Physiology)

定量生理学(Quantitative Physiology)

定 价:¥138.00

作 者: (中国)陈尚宾(Shangbin Chen),(俄罗斯)Alexey Zaikin(阿列克谢-扎伊金)
出版社: 华中科技大学出版社
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标 签: 暂缺

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ISBN: 9787568066785 出版时间: 2021-04-01 包装:
开本: 16开 页数: 字数:  

内容简介

  Stephen Hawking says that the next 21st century will be the century of complexity and indeed now Systems Biology or Medicine means dealing with complexity. Both genome and physiome have been emerged in studying complex physiological systems. Computational and mathematical modelling has been regarded as an efficient tool to boost understanding about the living systems in normal or pathophysiological states.This textbook introduces the students and researchers to the modelling and computational study of physiology (i.e. quantitative physiology), which is an increasingly important branch of systems biology. The topics cover basic methodology, case practices and advanced applications. This book aims to build multiscale model for investigating the function in living systems, or, how organisms, organ systems, organs, cells, and biomolecules carry out the chemical or physical functions that exist in a living system. Some of the models related on gene expression, calcium signalling, neural activity, blood dynamics and bone mechanics have been addressed. This book is devoted to set a paradigm for quantitative physiology by integrating biology, mathematics, physics and informatics etc.

作者简介

  陈尚宾博士,武汉光电国家研究中心副教授,博士生导师。2001年于湖北师范学院获物理学学士学位,2006年于华中科技大学获生物医学工程博士学位。2006年8月至今在华中科技大学工作;其间2008年2-5月在英国Bradford大学做访问学者,2010-2012在加拿大英属哥伦比亚大学(UBC)做博士后研究两年。其研究工作涉及神经光学成像、神经系统建模、定量生理学,已主持完成国家自然科学基金两项。已在Journal of Neuroscience,Biophysical Journal,Frontiers in Neuroscience等期刊发表第一作者(含通讯)论文十余篇。2007年荣获湖北省自然科学奖一等奖(排名5)。合作者Alexey Zaikin教授是世界*尖高校伦敦大学学院(UCL)系统医学和应用数学讲席教授,研究兴趣包括系统生物学、理论生物物理学、生物非线性动力学和随机性建模等。Zaikin教授已发表学术论文逾百篇,包含Physical Review Letters多篇,谷歌学术统计h指数29。Zaikin教授自2016年以来短期受聘于华中科技大学工程科学学院,参与《定量生理学》课程教学。

图书目录

Part I Applied Methodology
1 Introduction to Quantitative Physiology . . . . . . . . 3
1.1 Understanding Physiology . . . . . . . . . . . . . . . . 3
1.2 Towards Quantitative Science . . . . . . . . . . . . . 4
1.3 FromGenome to Physiome . . . . . . . . . . . . . . . 5
1.4 Dealing with Complexity . . . . . . . . . . . . . . . . . 6
1.5 Why It Is Timely to Study Quantitative Physiology . . . . . . . . . . 6
1.5.1 Multi-Omic Revolution in Biology . 6
1.5.2 Big Data and PersonalisedMedicine 7
1.5.3 Genetic Editing and Synthetic Biology . . . . . . . . . .  8
1.6 Questions . . . . . 8
References . . . . . . . . . . 8
2 Systems and Modelling . . . . . . . . . 11
2.1 Modelling Process . . . . . . . .  11
2.2 Physiological Organ Systems . . . . . . . . 13
2.3 EquationModels . . . . . . . . . . 14
2.4 Using ODEs in Modelling Physiology . . . . . . 16
2.4.1 Modelling Oscillations . . . . . . . . . . . 16
2.4.2 Linear Stability Analysis . . . . . . . . . . 16
2.4.3 Solving ODEs with the δ-Function . 17
2.5 Conservation Laws in Physiology . . . . . . . . . . 18
2.5.1 Conservation ofMomentumand Energy . . . . . . . . .18
2.5.2 Boxing With and Without Gloves . . 19
2.5.3 RotationalMovement . . . . . . . . . . . . 20
2.6 Questions . . . . . 20
References . . . . 21
3 Introduction to Basic Modelling . . . . . . . 23
3.1 Building a SimpleMathematicalModel . . . . . 23
3.1.1 Model of Falling Flea . . . . . . . . . . . . 23
3.1.2 Scaling Arguments. . . . . .  25
3.1.3 Example: How High Can an Animal Jump? . . . . . . .  25
3.1.4 Example: How Fast Can we Walk before Breaking into a Run? . . . 25
3.2 Models that InvolveMetabolic Rate . . . . . . . . 26
3.2.1 Modelling Metabolic Rate . . . . . . . . 26
3.2.2 Example:Why do Large Birds find it Harder to Fly? . . . . . . . . . . . 27
3.2.3 Ludwig von Bertalanffy’s GrowthModel . . . . . . .  28
3.3 Questions . . . . . 29
Reference . . . . . . . . . . 29
xv
xvi Contents
4 Modelling Resources 31
4.1 Open Courses. . 31
4.2 Modelling Software . . . . . . .  31
4.3 Model Repositories . . . . . . . 34
4.4 Questions . . . . . 35
References . . . . . . . . . . 35
Part II Basic Case Studies
5 Modelling Gene Expression . . . . . . .  39
5.1 Modelling Transcriptional Regulation and Simple Networks . . . . . . . . . . . . . 39
5.1.1 Basic Notions and Equations. . . . . . . 39
5.1.2 Equations for Transcriptional Regulation . . . . . . .  39
5.1.3 Examples of Some Common Genetic Networks . . . . . .  41
5.2 Simultaneous Regulation by Inhibition and Activation . . . . . . . .. 42
5.3 Autorepressor with Delay. . . . . . . .  43
5.4 Bistable Genetic Switch . . . . . . . . . 44
5.5 Questions . . . . . 44
References . . . . . . . . . . 45
6 Metabolic Network . . 47
6.1 Metabolismand Network . . . . . . .  47
6.2 ConstructingMetabolic Network . . . . . . . . . . 49
6.3 Flux Balance Analysis . . . . . . . .  50
6.4 MyocardialMetabolic Network. . . . . . . . . . . . 51
6.5 Questions . . . . . 51
References . . . . . . . . . . 52
7 Calcium Signalling . . 53
7.1 Functions of Calcium . . . . . .  53
7.2 Calcium Oscillations . . . . . . . .  54
7.3 CalciumWaves 59
7.4 Questions . . . . . 59
References . . . . . . . . . . 60
8 Modelling Neural Activity . . . . . . .  61
8.1 Introduction to Brain Research . . . . . . . . . . . . 61
8.2 The Hodgkin–Huxley Model of Neuron Firing . . . . . . . . . 62
8.3 The FitzHugh–Nagumo Model: A Model of the HH Model . . . . . . . . . . . . . 63
8.3.1 Analysis of Phase Plane with Case Ia = 0 . . . . . . . .  63
8.3.2 Case Ia > 0 and Conditions to Observe a Limit Cycle . . . . . . . . . . 64
8.4 Questions . . . . . 65
References . . . . . . . . . . 66
9 Blood Dynamics . . . . 67
9.1 Blood Hydrodynamics . . . . . . .  67
9.1.1 Basic Equations . . . . . . . . . . . . . . . . . 67
9.1.2 Poiseuille’s Law . . . . . . . . 67
9.2 Properties of Blood and ESR . . . . . . .  68
9.3 Elasticity of Blood Vessels . . . . . .  69
9.4 The PulseWave 69
9.5 Bernoulli’s Equation and What Happened to Arturo Toscanini in 1954 . . . . 70
9.6 The Korotkoff Sounds . . . . . . . .  71
9.7 Questions . . . . . 71
Reference . . . . . . . . . . . 72
Contents xvii
10 Bone and Body Mechanics . . . . .  73
10.1 Elastic Deformations and the Hooke’s Law. . 73
10.2 Why Long Bones are Hollow or Bending of Bones . . . . . . . . 74
10.3 Viscoelasticity of Bones . . . . . . .  77
10.4 Questions . . . . . 83
Reference . . . . . . . . . . 83
Part III Complex Applications
11 Constructive Effects of Noise . . . . . . . 87
. . . . . . . . . .

12 Complex and Surprising Dynamics in Gene Regulatory Networks . . . . . . . . . . 147
. . . . . . . . . .

13 Modelling Complex Phenomena in Physiology . . . 189
13.1 Cortical Spreading Depression (CSD) . . . . . . 189
13.1.1 What is CSD . . . . . . . .  189
13.1.2 Models of CSD . . . . . . . 189
13.1.3 Applications of CSDModels . . . . . . 192
13.1.4 Questions. . . . . . . . 196
13.2 Heart Physiome 197
13.2.1 Cardiovascular System. . . . . . . . . . . . 197
13.2.2 Heart Physiome . . . . . . . . . . . . . . . . . 198
13.2.3 Multi-Level Modelling . . . . . . . . . . . . 199
13.2.4 Questions. . . . . . . 201
13.3 Modelling of Kidney Autoregulation . . . . . . . 202
13.3.1 Renal Physiology . . . . . . .  202
13.3.2 Experimental Observations . . . . . . . . 204
13.3.3 Model of Nephron Autoregulation . . 205
13.3.4 Questions. . . . . . . . . .209
13.4 Brain Project . . 209
13.4.1 Mystery of Brain . . . . . . . . . . . . . . . . 209
13.4.2 Brain Projects . . . . . . . . . . . . . . . . . . . 210
13.4.3 Brain Simulation . . . . . . .  212
13.4.4 Mammalian Brain as a Network of Networks . . . . . . .215
13.4.5 Calculation of Integrated Information . . . . . . . . . . . . . . 223
13.4.6 Astrocytes and Integrated Information Theory of Consciousness . . 224
13.4.7 Questions. . . . . . . . . . . . 233
References . . . . . . . . . . 233

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