Computational and Systems Biology
There is widespread agreement that computational and new systems theoretic methods are crucial for the future of biomedical sciences. This need arises from the inherent complexity of biological systems coupled with the enormous amount of data being collected by novel high-throughput experimental approaches. For example, the signaling pathways that enable cells to respond to their environments contain multiple biochemical steps, are highly nonlinear, and are regulated by different types of control mechanisms. Complex biochemical networks regulate and coordinate almost all cellular processes including such things as the cell cycle and chemotaxis. In addition, the fields of cell and molecular biology are rapidly becoming more quantitative. This transition is being driven by new experimental techniques including fluorescence imaging that allow measurements to be made at the level of individual cells. These developments have spurred a renewed interest in computational models of both cellular processes and those that occur at the organ level. The ideas developed from studying dynamical systems and stochastic processes as well as the development of graphical methods provide powerful techniques for understanding the complex behavior observed at the cellular and molecular level. The application of these methodologies is fostered at this juncture by the increasing power of computational methods and equipment.
The emerging field of systems biology integrates high-throughput experimental techniques with computational modeling to develop a mechanistic understanding of the complex interactions of genes, proteins and cell elements that coordinate and regulate cellular behavior. An important outcome from this line of research is the development of mathematical models that can be tested experimentally and used to predict the behavior of a complex biological system after an experimental or environmental challenge. Another important outcome would be the capability to control the system by finding the optimal inputs that would lead to the desired results. It is not only vitally important but also entirely feasible for UNC to develop a commanding and unique presence in systems biology in order to maintain its position at the forefront of biomedical research. At UNC, widespread campus interest is already apparent indicated by faculty from eight departments already participating in the Center.
Mission statement of the center
The Center will foster research that develops methods to deal with and understand the unique features found in complex biological systems (modularity, hierarchy, robustness, ability to adapt and evolve). It will emphasize mechanistic mathematical models that integrate different levels of organization (e.g. molecular systems to cell behavior). The Center will be structured both to carry on research and to enhance the educational goals of the Bioinformatics and Biophysics Programs. Thus, a key component of the Center will be the research training of undergraduate and graduate students. Students from both Molecular and Cellular Biophysics and the Bioinformatics and Computational Biology training programs will be able to perform rotations in the Center. In this and other ways, the Center will complement and synergize with current efforts in the Center for Genome Sciences and elsewhere.
