Computational biomedicine: modelling the human body
Saved in:
| Other Authors: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Oxford
Oxford Univ. Press
2014
|
| Subjects: | |
| Online Access: | Klappentext Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XIII, 278 S. Ill., graph. Darst. |
| ISBN: | 9780199658183 |
Staff View
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| adam_text | A student-focused, practice-oriented overview of
the burgeoning field of computational biomedicine.
Drawing upon remarkable advances in information
technology, computer, mathematical, physical, chemical
and engineering science, data management, and high
performance computing, Computational Biomedicine
unifies the different strands of a broad-ranging subject
to demonstrate its power as a tool with the potential
to revolutionize our understanding of the human body,
and the therapeutic strategies available to maintain
and protect it.
Written and edited by a team of world-leading experts
in the field, it explores the modelling of physiological
systems at different scales-molecules, cells, tissues,
organs-before considering the issues around biomedical
computing, and data collection and analysis. It empha-
sizes how a theoretical understanding of computational
biomedicine translates into practice, with illustrative
examples and case studies used throughout.
► The first text to make this burgeoning area of multi-
disciplinary research accessible to the student reader
► Brings together the fields of mathematics, physics,
computer science, biology, chemistry, engineering,
and medicine to provide a single, coherent view
of the subject
► An emphasis throughout on the power of computa-
tional biomedicine as a tool demonstrates how theory
can translate into clinical benefit
Computational Biomedicine is the perfect introduction
to the subject for anyone new to the field, from student
to experienced research scientist.
Peter Coveney holds a Chair in Physical Chemistry,
is Director of the Centre for Computational Science, and
is an Honorary Professor in Computer Science at University
College London. He is also Professor Adjunct within the
Medical School at Yale University.
Vanessa Dfaz-Zuccarini is a lecturer in Bioengineering
at University College London. Working at the interface of
systems biology and engineering, she is the founder of
the Multiscale Cardiovascular Engineering Group in UCL,
which she now leads.
Peter Hunter FRS is Professor of Engineering Science
and Director of the Bioengineering Institute at the
University of Auckland, New Zealand, and co-Director of
Computational Physiology at the University of Oxford, UK.
Marco Viceconti is Professor of Biomechanics in the
department of mechanical engineering, and scientific
director of the Insigneo institute for in silico medicine,
at the University of Sheffield, UK. He is also the Executive
Director of the VPH Institute.
CONTENTS
Contributing Authors xü
1 Introduction 1
1.1 Introduction 1
1.2 Systems Biology 2
1.3 Initiatives for Modelling Human Physiology 3
1.4 Book Synopsis 3
References 5
2 Molecular Foundations of Computational
Bioscience 6
2.1 Introduction 6
2.2 DNA and its Data Formats 8
2.3 RNA and its Data Formats 13
2.4 Proteins and their Data Formats 18
2.5 Metabolism, Metabolites, and their
Databases 21
2.6 Integrating Different Data Types and
Sources 22
2.7 Management of Omics Data Types 24
Box 2.1 Example of the Use of Multiple
Databases to Answer a Specific Research
Question 25
2.8 Software Systems: Security and
Interoperability 29
2.9 Conclusions 30
Recommended Reading 32
References 32
3 From Genotype to Phenotype
3.1 Introduction
3.2 Quantitative Genetics: A Brief Introduction
3.3 Systems Genetics
Box 3.1 A cGP Model of the Action
Potential of a Heart Muscle Cel!
Box 3.2 Refining the Genotype-to-
Parameter Map: From Nucleotide Mutation
to Protein Conformation to State Switching
in Ion Channels
3.4 Implementing cGP Models 44
Box 3.3 Monte Carlo Methods 46
Box 3.4 Models of Gene Regulation 48
3.5 Some cGP Applications 49
3.6 Linking cGP Models to Data 51
3.7 Conclusions 56
Recommended Reading 57
References 57
4 Image-Based Modelling 59
4.1 Introduction 59
4.2 Image-Based Modelling 66
4.3 Simulating the Physics of Image Formation 75
4.4 Statistical Atlases, Population Imaging, and
Modelling 78
4.5 Open-Source Tools for I mage-Based
Modelling 79
4.6 Conclusions 81
Recommended Reading 82
References 82
5 Modelling Cell Function 84
5.1 Introduction 84
5.2 General Functions of Cells 87
53 Fundamentals of Reactions in Cells 88
Box 5.1 The Cell as a Complex System 89
5.4 Formalisms and Abstractions in Cell
Modelling 92
5.5 Modelling Approaches 94
Box 5.2 Compartmentai Models of the
Cell Using ODEs 96
5.6 Simulation Tools 101
5.7 Reproducible Cell Modelling
Box 5.3 Case Study: A Reproducible
Validated Model of Hepatic Clearance
Using ODEs 106
5.8 Conclusions 109
Recommended Reading 109
References 109
Contents
6 Modelling Tissues and Organs 111
6.1 Introduction 111
6.2 Modelling Epithelia 112
6.3 Cardiac Modelling 119
Box 6.1 The Navier-Stokes Equations
for Fluid Flow 122
6.4 Gl Tract Modelling 124
6.5 Modelling Kidney Function and
Homeostasis 128
6.6 General Homeostasis and Blood-Pressure
Regulation 134
6.7 Conclusions 135
Recommended Reading 136
References 136
7 Multi-Scale Modelling and Simulation 138
7.1 Introduction: Multi-Scale Modelling in
Computational Physiology 138
7.2 Why Multi-Scale Modelling? 141
7.3 A Framework for Multi-Scale Modelling
and Computing 142
7.4 Scale Bridging 148
7.5 Multi-Scale Computing 150
7.6 Case Study of a Multi-Scale Model:
In-Stent Restenosis in Coronary Arteries 152
7.7 Conclusions 158
Recommended Reading 159
References 159
8 Workflows: Principles, Tools, and Clinical
Applications 161
8.1 Introduction 161
8.2 Computational Workflows 162
8.3 Implementing Workflows 169
8.4 Provenance 174
8.5 Examples of Scientific Workflows 177
8.6 Some Key Considerations in Workflow
Design 182
8.7 Conclusions 184
List of Projects Referenced 184
Recommended Reading 184
References 184
9 Distributed Biomedical Computing 186
9.1 Introduction 186
9.2 Parallel Applications 187
9.3 The Computational Ecosystem 189
9.4 Computing Beyond the Desktop 190
9.5 Executing Simulations in a High-
Performance Environment 191
9.6 Case Study: Calculating Drug
Binding Affinities 193
9.7 Computational Infrastructures 194
9.8 Distributed Applications 197
9.9 Orchestrating Workflows from
Distributed Applications 202
9.10 Case Study. Computational Investigations
of Cranial Haemodynamics 203
9.11 Conclusions 205
Recommended Reading 206
References 206
10 Security and Privacy in Sharing Patient Data 207
10.1 introduction 207
10.2 The Legal Background 209
Box 10.1 Regulations and Directives 209
10.3 A Brief Overview of Information Security
Concepts 214
Box 10.2 Information Security Overview 214
10.4 The Data-Sharing Life Cycle 215
10.5 Data-Sharing Platform Architectures 218
10.6 Conclusions 228
Recommended Reading 230
References 230
11 Toward Clinical Deployment: Verification
and Validation of Models 232
11.1 Introduction: Health Technology
Assessment 232
Box 11.1 EU Definition of a Medical
Device 234
11.2 Code and Model Verification 234
11.3 Sensitivity Analysis 235
11A Model Validation 236
11.5 Validation of Integrative Models 238
11.6 Clinical Accuracy 239
11.7 Efficacy, Risk, and Cost-Benefit
Analysis 243
11.8 Impact 244
11.9 Sustainability 247
11.10 Conclusions 250
Recommended Reading 251
References 251
Online Resource Centre
Appendix: Markup Languages, Standards, and
Model Repositories 252
A.1 Introduction 252
A.2 Infrastructure for Computational
Biomedicine 253
A.3 Syntax, Semantics, and Annotation of
Models 254
A.4 Markup Languages 256
A.5 Model Repositories 261
A.6 Conclusions 263
References 264
Glossary 265
Index 273
|
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| spelling | Computational biomedicine modelling the human body ed. by Peter V. Coveney ... Biomedicine Oxford Oxford Univ. Press 2014 XIII, 278 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Medical sciences / Computer simulation Medical technology Biomedical engineering Bioinformatik (DE-588)4611085-9 gnd rswk-swf Biomedizin (DE-588)4647152-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Biomedizin (DE-588)4647152-2 s Bioinformatik (DE-588)4611085-9 s DE-604 Coveney, Peter V. (DE-588)173625053 edt Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027476223&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027476223&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Computational biomedicine modelling the human body |
| title_alt | Biomedicine |
| title_auth | Computational biomedicine modelling the human body |
| title_exact_search | Computational biomedicine modelling the human body |
| title_full | Computational biomedicine modelling the human body ed. by Peter V. Coveney ... |
| title_fullStr | Computational biomedicine modelling the human body ed. by Peter V. Coveney ... |
| title_full_unstemmed | Computational biomedicine modelling the human body ed. by Peter V. Coveney ... |
| title_short | Computational biomedicine |
| title_sort | computational biomedicine modelling the human body |
| title_sub | modelling the human body |
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