The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools.
Novel Approaches to Fighting Cancer
Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research.
Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications
Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects:
- Categorising tumours
- Finding new targets
- Designing improved and tailored therapeutic strategies
Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.
Table of Contents
Introduction: Why Systems Biology of Cancer? Basic Principles of the Molecular Biology of Cancer. Experimental High-Throughput Technologies for Cancer Research. Bioinformatics Tools and Standards for Systems Biology. Exploring the Diversity of Cancers. Prognosis and Prediction: Towards Individualised Treatments. Mathematical Modelling Applied to Cancer Cell Biology. Mathematical Modelling of Cancer Hallmarks. Cancer Robustness: Facts and Hypotheses. Cancer Robustness: Mathematical Foundations. Finding New Cancer Targets. Conclusion. Appendices. Glossary. Bibliography. Index.
Emmanuel Barillot, Laurence Calzone, Philippe Hupe, Jean-Philippe Vert, and Andrei Zinovyev are all with the Institut Curie in Paris, France.
"There is a tremendous amount of biological and biochemical detail in this book, and yet (gratifyingly and perhaps surprisingly) considerable attention is paid to mathematical definitions …"
—John Adam, Mathematical Reviews, August 2013
"An up-to-date, comprehensive and very readable overview, this book has plenty for everyone interested in computational systems biology of cancer. Almost all important topics are introduced and explained, and pointers are given to further work. The bibliography is outstanding. Think of this as your guide book to the field, as well as a way to get started in it."
—Terry Speed, Professor of Statistics, University of California, Berkeley, USA, and Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
"This book deals with an important and very timely topic: The ongoing struggle against cancer can benefit greatly from the novel high-throughput technologies that are rapidly becoming more accessible. However, in order to make effective use of the data that these technologies produce, sophisticated computational methods that address the cancer disease on the system level are needed. The authors have made substantial and useful effort to describe the state of the art of these computational methods in an accessible and clear way. The book is a much-needed contribution to modern cancer analysis and to the emerging discipline of systems biology."
—Ron Shamir, Professor of Bioinformatics, Tel Aviv University, Israel
"This is the first book specifically focused on computational systems biology of cancer with coherent and proper vision on how to tackle this formidable challenge. I would like to congratulate the authors for their visions and dedications."
—Hiroaki Kitano, President, The Systems Biology Institute; President and Chief Operating Officer, Sony Computer Science Laboratories, Inc.; and Professor, Okinawa Institute of Science and Technology, Japan