
Cancer Bioinformatics : From Therapy Design to Treatment
by Editor: Sylvia Nagl (University College London, UK)Rent Textbook
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Summary
Table of Contents
Preface | |
List of Contributors | |
Cancer Systems | |
A Path to Knowledge: from Data to Complex Systems Models of Cancer | |
Conceptual foundations: biological complexity | |
A taxonomy of cancer complexity | |
Modelling and simulation of cancer systems | |
Data standards and integration | |
Concluding remarks | |
Theory of Cancer Robustness | |
Robustness: the fundamental organizational principle of biological systems | |
Underlying mechanisms for robustness | |
Intrinsic features of robust systems: evolvability and trade-offs | |
Cancer as a robust system | |
Therapy strategies | |
A proper index of treatment efficacy | |
Computational tools | |
Conclusion | |
Developing an Integrated Informatics Platform for Cancer Research | |
Background | |
The challenge | |
The UK National Cancer Research Institute (NCRI) informatics platform | |
Developing the informatics platform | |
Benefits of the platform | |
Conclusions | |
In silico Models | |
Mathematical Models of Cancer | |
Growth models | |
A very brief tour of cellular automata | |
Angiogenesis models | |
Treatment response models | |
Dynamic pathways models | |
Other models | |
Simulations of complex biological systems | |
Concluding remarks | |
Some Mathematical Modelling Challenges and Approaches in Cancer | |
Introduction | |
Multiscale modelling | |
Tumour vascular modelling | |
Population models | |
Conclusion | |
Computer Simulation of Tumour Response to Therapy | |
Introduction | |
Tumour growth simulation | |
Radiotherapy response simulation | |
Chemotherapy response simulation | |
Simulation of tumour response to other therapeutic modalities | |
Simulation of normal tissue response to antineoplastic interventions | |
Integration of molecular networks into tumour behaviour simulations | |
Future directions | |
Structural Bioinformatics in Cancer | |
Introduction | |
Macromolecular crystallography | |
Molecular modelling | |
Conclusions | |
In vivo Models | |
The Mouse Tumour Biology Database: an Online Resource for Mouse Models of Human Cancer | |
Introduction | |
Background | |
Database content | |
Data acquisition | |
Using the MTB database | |
Connecting the MTB database with related databases | |
Summary | |
Bioinformatics Approaches to Integrate Cancer Models and Human Cancer Research | |
Background | |
The MMHCC Informatics at the outset of the programme | |
Initial NCI bioinformatics infrastructure development | |
Future directions for informatics support | |
Summary | |
Data | |
The FAPESP/LICR Human Cancer Genome Project: Perspectives on Integration | |
Introduction | |
The FAPESP/LICR Human Cancer Genome Project | |
An integrated view of the tumour transcriptome | |
Summary | |
Today's Science, Tomorrow's Patient: the Pivotal Role of Tissue, Clinical Data and Informatics in Modern Drug Development | |
Introduction | |
A new national strategy for the provision of tissue annotated with clinical information to meet current and future needs of academic researchers and industry | |
The NCRI National Cancer Tissue Resource for cancer biology and treatment development | |
A potential future world-class resource integrating research and health service information systems and bioinformatics for cancer diagnosis and treatment | |
A proposed information system architecture that will meet the challenges and deliver the required functionality: an overview | |
Consent and confidentiality: ensuring that the NCTR is embedded in the UK's legal and ethical framework | |
Concluding remarks: future challenges and opportunities | |
Ethics | |
Software Design Ethics for Biomedicine | |
The problem: software and research | |
Risk identification | |
Biomedical software example | |
Is an ethical risk analysis required? | |
Details of SoDIS | |
A SoDIS analysis of the biomedical software example | |
Conclusion | |
Ethical Issues of Electronic Patient Data and Informatics in Clinical Trial Settings | |
Introduction | |
Ethical aspects of using patient-identifiable health data | |
Legislation and policies pertaining to patient-identifiable health data | |
Using anonymized and pseudonymized data | |
Protecting personal health data | |
Pharmacogenomics and Cancer: Ethical, Legal and Social Issues | |
Introduction | |
Getting pharmacogenomic tests and drugs to market | |
Cost and coverage issues | |
Ethical challenges of pharmacogenomics | |
Conclusion | |
Index | |
Table of Contents provided by Publisher. All Rights Reserved. |
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