Computational Systems Biology of Cancer

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

• 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.