Hjem

1. Introduction2. Molecular Foundations of Computational Bioscience2.
1 Introduction2.
2 Types of Omics Data2.
3 Databases and Data Sources2.
4 Management of Omics Data Types2.
5 Software Systems and Interoperability2.
6 Clinical Phenotypes, Security and Data Sharing2.
7 Conclusions3. Understanding the Genotype-Phenotype Relationship3.
1 Introduction3.
2 Quantitative Genetics Theory3.
3 Systems Genetics3.
4 Implementing CGP Models3.
5 CGP Applications3.
6 Linking CGP Models to Data3.
7 Conclusions4. Image Based Modelling4.
1 Introduction4.
2 Biomedical Imaging Techniques4.
3 Image Based Modelling4.
4 Medical Image Simulation4.
5 Statistical Atlases, Populational Imaging and Modelling4.
6 Open Source Image Modelling Tools4.
7 Conclusions5. Modelling Cell Function5.
1 Introduction5.
2 General Cell Functions5.
3 Cell Fundamentals5.
4 Levels of Abstraction5.
5 Cell Simulation5.
6 Approaches to Modelling and Simulation5.
7 Simulation Tools5.
8 Example: An Agent Model in Skeletal Mechanobiology5.
9 Reproducible Modelling: Ordinary Differential Equations5.
10 Conclusions6. Modelling Tissues and Organs6.
1 Introduction6.
2 Modelling Epithelia6.
3 Cardiac Modelling6.
4 Modelling the Gastro-Intestinal Tract6.
5 Modelling Kidney Function and Homeostasis6.
6 General Homeostasis and Blood Pressure Regulation6.
7 Conclusions7. Multi-Scale Modelling7.
1 Introduction7.
2 Why Multi-Scale Modelling?7.
3 A Framework for Multi-Scale Modelling and Computing7.
4 Scale Bridging7.
5 Multi-Scale Computing7.
6 Example of a Multiscale Model: In-Stent Restenosis in Coronary Arteries7.
7 Conclusions8. Workflows: Principles, Tools and Clinical Applications8.
1 Introduction: What is a Workflow?8.
2 Computational Workflows8.
3 Workflow Implementations8.
4 Provenance8.
5 Examples of Scientific Workflows8.
6 Key Considerations8.
7 Conclusions9. Distributed Biomedical Computing9.
1 Introduction9.
2 Parallel Applications9.
3 The Computational Ecosystem9.
4 Computing Beyond the Desktop9.
5 Simulations in a High Performance Computing Environment9.
6 Case Study
1: Calculating Drug Binding Affinities9.
7 Computational Infrastructures9.
8 Distributed Applications9.
9 Orchestrated Workflows from Distributed Applications9.
10 Case Study
2: Computational Investigations of Cranial Haemodynamics9.
11 Conclusions10. Managing Security and Privacy of Patient Data Sharing Platforms10.
1 Introduction10.
2 Legal Background10.
3 Brief Overview of Information Security Concepts10.
4 Common Data Sharing Requirements10.
5 The Data Sharing Lifecycle10.
6 Data Warehousing Architecture10.
7 Conclusions11. Toward Clinical Deployment: Verification and Validation of Models11.
1 Introduction: Technology Assessment versus Health Assessment11.
2 Code and Model Verification11.
3 Sensitivity Analysis11.
4 Model Validation11.
5 Validation of Integrative Models11.
6 Clinical Accuracy11.
7 Efficacy, Risk and Cost-Benefit11.
8 Impact11.
9 Sustainability11.
10 ConclusionsAppendix: Modelling Standards and Model RepositoriesA.
1 IntroductionA.
2 Infrastructure for Computational BiomedicineA.
3 Syntax, Semantics and Annotation of ModelsA.
4 Markup LanguagesA.
5 Model RepositoriesA.
6 Conclusions