New Challenges for Cancer Systems Biomedicine

It becomes increasingly evident that the tools to construct such complex models include, not only bioinformatics and modern applied statistics, as is unanimously agreed, but also other interdisciplinary fields of science, notably, Mathematical Oncology, Systems Biology and Theoretical Biophysics. The aim of this book is not only to illustrate the state of the art of tumor systems biomedicine, but also and mainly to explicitly capture the fact that a increasing number of biomedical scientists is now directly working on mathematical modeling, and a larger number are collaborating with bio-mathematical scientists. Moreover, a number of biomathematicians started working in biomedical institutions. The book is characterized by a coherent view of tumor modeling, based on the concept that mathematical modeling is (with medicine and molecular biology) one of the three pillars of molecular medicine. Indeed this volume is characterized by a well-structured presence of a large number of biomedical scientists directly working in Mathematical or Systems Biomedicine, and of a number biomathematicians working in hospitals. This give to this book an unprecedented tone, providing an original interdisciplinary insight into the biomedical applications. Finally, all biomedical contributors were asked to briefly summarize in one section of their contributes their point of view on her/his own interactions with quantitative scientists working in Systems Biomedicine. The future of oncology seems to lie in Molecular Medicine (MM). MM is a new science based on three pillars. Two of them are evident in its very name and are well known: medical science and molecular biology. However, there is a general unawareness that MM is firmly based on a third, and equally important, pillar: Systems Biomedicine. Currently, this term denotes multilevel, hierarchical models integrating key factors at the molecular, cellular, tissue, through phenotype levels, analyzed to reveal the global behavior of the biological process under consideration. It becomes increasingly evident that the tools to construct such complex models include, not only bioinformatics and modern applied statistics, as is unanimously agreed, but also other interdisciplinary fields of science, notably, Mathematical Oncology, Systems Biology and Theoretical Biophysics.