Aiming at understanding the dynamic interactions between components of a cell, between cells and their interaction with the environment, cancer systems biology is an approach by which biomedical questions are addressed through integrating experiments in iterative cycles with mathematical modeling, simulation and theory. Modeling is not the final goal, but is a tool to increase understanding of the system, to develop more directed experiments and finally to enable predictions.
This definition of cancer systems biology matches closely the definition of the EraSysBio consortium of 16 European ministries, funding bodies and project management agencies from 13 countries (www.erasysbio.net
, strategy paper, page 6).
The most popular definitions of systems biology refer to “dynamics”, “mechanisms”, “principles”, and “behaviors”. The complexity of biological systems/functions arises from the interaction of a myriad of nonlinear spatio-temporal phenomena and components. The fact that most cellular processes, such as cell-cycle control, cell differentiation and apoptosis, are inherently dynamical, highlights the need for integrating mathematical modeling into life science and clinical research. A systems biology approach can help identify and analyze the principles, laws and mechanisms underlying the behavior of biological systems.
The participants of the strategic workshop concluded that advancing biomedical applications through systems biology approaches requires the development of new theoretical methodologies, such as novel techniques for data-based system identification, theoretical concepts for the design of experiments, good methods for hypothesis testing, theoretical frameworks to couple processes occurring at (and across) different spatial and temporal scales, and effective algorithms to solve problems of computational complexity.