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Cancer Systems Biology, Bioinformatics and Medicine
Research and Clinical Applications
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Main description:

This teaching monograph on systems approaches to cancer research and clinical applications provides a unique synthesis, by world-class scientists and doctors, of laboratory, computational, and clinical methods, thereby establishing the foundations for major advances not possible with current methods.  Specifically, the book: 1) Sets the stage by describing the basis of systems biology and bioinformatics approaches, and the clinical background of cancer in a systems context; 2) Summarizes the laboratory, clinical, data systems analysis and bioinformatics tools, along with infrastructure and resources required; 3) Demonstrates the application of these tools to cancer research; 4) Extends these tools and methods to clinical diagnosis, drug development and treatment applications; and 5) Finishes by exploring longer term perspectives and providing conclusions. This book reviews the state-of-the-art, and goes beyond into new applications. It is written and highly referenced as a textbook and practical guide aimed at students, academics, doctors, clinicians, industrialists and managers in cancer research and therapeutic applications. Ideally, it will set the stage for integration of available knowledge to optimize communication between basic and clinical researchers involved in the ultimate fight against cancer, whatever the field of specific interest, whatever the area of activity within translational research.


Feature:

The world’s top experts describe systems approaches to cancer research and application

Is uniquely organized to unify all aspects from laboratory to clinic

Demonstrates how systems approaches build upon and greatly extend and unify current research practices

Demonstrates that cancer systems approaches form a unified field that has already produced major applications

A full range of subjects is covered, spanning laboratory, clinical and medical approaches


Back cover:

This teaching monograph on systems approaches to cancer research and clinical applications provides a unique synthesis, by world-class scientists and doctors, of laboratory, computational, and clinical methods, thereby establishing the foundations for major advances not possible with current methods.  Specifically, the book: 1) Sets the stage by describing the basis of systems biology and bioinformatics approaches, and the clinical background of cancer in a systems context; 2) Summarizes the laboratory, clinical, data systems analysis and bioinformatics tools, along with infrastructure and resources required; 3) Demonstrates the application of these tools to cancer research; 4) Extends these tools and methods to clinical diagnosis, drug development and treatment applications; and 5) Finishes by exploring longer term perspectives and providing conclusions. This book reviews the state-of-the-art, and goes beyond into new applications. It is written and highly referenced as a textbook and practical guide aimed at students, academics, doctors, clinicians, industrialists and managers in cancer research and therapeutic applications. Ideally, it will set the stage for integration of available knowledge to optimize communication between basic and clinical researchers involved in the ultimate fight against cancer, whatever the field of specific interest, whatever the area of activity within translational research.


Contents:

PART I – Introduction and background.- 1. Introduction to systems approaches to cancer.- 1.1 Cancer and systems approaches.- 1.2 Laboratory, clinical, data and educational resources.- 1.3 Bioinformatics and systems biology analysis.- 1.4 Diagnosis and treatment applications.- 1.5 Perspectives and conclusions.- 1.6 References.- 2. Cancer: clinical background and key challenges.- 2.1 Introduction.- 2.2 Pathology integration in cancer biology systems.- 2.3 Technological approaches to morphology and pathology.- 2.4 Treatments.- 2.5 Major cancers, diagnosis, disease-specific supplementary classifications, and treatment implications.- 2.6 Systems biology of cancer: key challenges for the future.- 2.7 Acknowledgements.- 2.8 References.- PART II – Laboratory, clinical, data and educational resources.- 3. Global molecular and cellular measurement technologies.- 3.1.  Introduction – the need for systems biology predictive models.- 3.2.  Sample preparation.- 3.3. Analysis of the genome.- 3.4.  Proteomics.- 3.5  Functional studies.- 3.6 Overall determining factors and future outlook.- 3.7 Acknowledgements.- 3.8 References.- 3.9 Abbreviations.-

4. Cell lines, tissue samples, model organisms, biobanks.- 4.1 Introduction.- 4.2 Human cell lines.- 4.3 Model organisms.- 4.4 Patient biobanks.- 4.5 Role of interactome maps and crucial pathways.- 4.6 Integration into systems and computational approaches.- 4.7 The future: data integration to systems-level experiments.- 4.8 References.- 5. Expression and genetic variation databases for cancer research.- 5.1 Introduction.- 5.2 Genetic variation.- 5.3 Gene expression.- 5.4 Informatics coordination by international consortia.- 5.5 References.- 6. Education and Research Infrastructures.- 6.1 The challenge.- 6.2 The actors.- 6.3 Training and education of the stakeholders.- 6.4 Organization of cancer research centres and their cross-disciplinary activities.- 6.5 Conclusion.- 6.6 Acknowledgements.- 6.7 References.- PART III – Bioinformatics and systems biology analysis.- 7. Mathematical tools in cancer signalling systems biology.- 7.1 Introduction.- 7.2 The systems approach.- 7.3 Discussion.- 7.4 Acknowledgements.- 7.5 References.- 7.6 Appendix.- 8. Computational tools for systems biology.- 8.1 Introduction.- 8.2 Standards in systems biology.- 8.3 Web Resources.- 8.4 Computational Tools.- 8.5 Visualizing networks.- 8.6 Workflows.- 8.7 Discussion.- 8.8 Acknowledgements.- 8.9 References.- 9. The hallmarks of cancer revisited through systems biology and network modeling.- 9.1 Introduction.- 9.2 Genome variation and instability revisited through genetic and genomic networks.- 9.3 Transcription and protein interaction networks revealed by modular cancer biomarkers.- 9.4 Growth, proliferation and apoptosis revisited through signalling network modeling.- 9.5 Sustained angiogenesis and metastasis revisited through multiscale modeling.- 9.6 The hallmarks of cancer extended to control of stress and metabolism.- 9.7 Conclusion and perspectives.- 9.8 Acknowledgements.- 9.9 References.- 10. Systems biology analysis of cell death pathways in cancer: how collaborative and interdisciplinary research helps.- 10.1 Introduction.- 10.2 Cell death pathways.- 10.3 Dysregulation of cell death pathways in cancer.- 10.4 Mathematical modelling of cell death pathways.- 10.5 Elements for interdisciplinary approaches to cancer research.- 10.6 How to share knowledge about systems biology approaches to cancers.- 10.7 Major collaborative efforts.- 10.8 Supporting collaborative research projects.- 10.9 Conclusion.- 10.10 Acknowledgements.- 10.11 References.- 11. Systems biology, bioinformatics and medicine approaches to cancer progression outcomes.-1 1.1 Introduction: The concept of pathway signatures.- 11.2 Identification of biological motifs from gene array data.- 11.3 From biological motifs to pathway activation.- 11.4 How realistic is modelling of carcinogenesis and tumour development in virtual tissues and organs?- 11.5 References.- 11.6 Websites.- 12. System dynamics at the physiological and tumour level.- 12.1 Introduction to mathematical modelling in cancer.- 12.2 Mathematical models in cancer.- 12.3 Model development.- 12.4 Iterative modelling of tumour systems.- 12.5 Experimental studies of tumour invasion.- 12.6 Tumour modelling collaborations.- 12.7 Detailed modelling example.- 12.8 Conclusions.- 12.9 References.- PART IV – Diagnosis, clinical and treatment applications.- 13. Diagnostic and prognostic cancer biomarkers: from traditional to systems approaches.- 13.1 Introduction.- 13.2 Role of biomarkers.- 13.3 Biomarkers for prediction of response to treatment.- 13.4 Biomarkers for prognosis.- 13.5 Biomarkers for monitoring.- 13.6 Measurement and analysis of biomarkers.- 13.7 Identification, standardization and validation of effective biomarkers.- 13.8 Annotated, high quality clinical samples.- 13.9 Analyses and simulations to predict and identify biomarkers.- 13.10 Approaches to data analyses in genomic studies.- 13.13 Pharmacokinetics and pharmacodynamics.- 13.14 Integrated approaches to biomarker discovery and development.- 13.15 References.- 14. Systems biology approaches to cancer drug development.- 14.1 Introduction.- 14.2 Model building.- 14.3 Case studies of modelling cellular networks.- 14.4 Modelling at cellular scales.- 14.5 Technologies used at Physiomics.- 14.6 Conclusion.- 14.7 References.- 15. Circadian rhythms and cancer chronotherapeutics .- 15.1 Circadian rhythms in health and diseases.- 15.2 Chronopharmacology, chronotolerance and chronoefficacy of anticancer drugs.- 15.3 From standard to personalized cancer chronotherapeutics.- 15.4 Conclusions and perspectives.- 15.5 Acknowledgements .- 15.6 References.- 16. Clinical applications of systems approaches.- 16.1 Chapter introduction.- 16.2 Systems biology approaches to identifying diagnostic, prognostic, and therapeutic biomarkers for cancer.- 16.3 Systems biology approaches to the design of combinatorial targeted therapy for cancer.- 16.4 The future of clinical trials: applying systems approaches to clinical trial design.- 16.5 References.- 17. Cancer robustness and therapy strategies.- 17.1 Introduction.- 17.2 Mechanisms for robustness.- 17.3 Mechanisms for cancer robustness.- 17.4 Robustness trade-offs.- 17.5 Theoretically-motivated therapy strategies.- 17.6 A proper index of treatment efficacy.- 17.7 Long-tail drugs.- 17.8 Conclusion.- 17.9 Acknowledgements.- 17.10 References.- PART V – Perspectives and conclusions.- 18. Synthetic biology and perspectives.- 18.1 Introduction.- 18.2 Synthetic biology for cancer research and applications.- 18.3 Synthetic biology applications to cancer.- 18.4 Review articles and workshops – integrated perspectives.- 18.5 Resources needed to support systems approaches to cancer research and diagnosis.- 18.6 Conclusions.- 18.7 References.- 19. Conclusions.- 19.1 Key points.- 19.2 Overall conclusions.- Index.

 

 


PRODUCT DETAILS

ISBN-13: 9789400715677
Publisher: Springer (Springer Netherlands)
Publication date: August, 2011
Pages: 494

Subcategories: General Issues, Oncology