PART I – Introduction and background -- 1. Introduction to systems approaches to cancer -- 2. Cancer: clinical background and key challenges -- PART II – Laboratory, clinical, data and educational resources -- 3. Global molecular and cellular measurement technologies -- 4. Cell lines, tissue samples, model organisms, biobanks -- 5. Expression and genetic variation databases for cancer research -- 6. Education and Research Infrastructures -- PART III – Bioinformatics and systems biology analysis -- 7. Mathematical tools in cancer signalling systems biology -- 8. Computational tools for systems biology -- 9. The hallmarks of cancer revisited through systems biology and network modeling -- 10. Systems biology analysis of cell death pathways in cancer: how collaborative and interdisciplinary research helps -- 11. Systems biology, bioinformatics and medicine approaches to cancer progression outcomes -- 12. System dynamics at the physiological and tumour level -- PART IV – Diagnosis, clinical and treatment applications -- 13. Diagnostic and prognostic cancer biomarkers: from traditional to systems approaches -- 14. Systems biology approaches to cancer drug development -- 15. Circadian rhythms and cancer chronotherapeutics -- 16. Clinical applications of systems approaches -- 17. Cancer robustness and therapy strategies -- PART V – Perspectives and conclusions -- 18. Synthetic biology and perspectives -- 19. Conclusions -- Index.

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.