Since the beginning of the computer era scientists have dreamed about using the power of computation to develop a predictive understanding (a computational “theory”) that could help explain the structure, function, and evolution of biological systems. Early attempts to develop computer models and the associated theory of biological systems were limited by our lack of a detailed molecular-level understanding of the mechanisms involved in even the most basic functions of growth, development, and genetic inheritance. Later, as modern molecular biology cracked the genetic code and biochemists filled in the chemical details of metabolism, available computer power became the bottleneck in extending our understanding towards prediction. Today new classes of supercomputers provide the necessary power and the recent dramatic advances in the availability of biological data yields information ranging from the DNA sequences of nearly 500 organisms to detailed snapshots of cellular machinery in action.
I will present the computational and computer science requirements of the emerging science of systems biology and how this new science may exploit technology under development for building petascale computers and life science grids. Of particular interest is the evolving mixture of life science computing applications that can efficiently exploit large-scale tightly coupled computing systems (e.g. macromolecular modeling) and those that can effectively exploit more distributed systems (e.g. genome annotation). The field of systems biology has an extremely broad range of computational methods and techniques in use, perhaps broader than any other scientific domain. This diversity of methods means that a rich collection of computing systems and software infrastructures is needed to match the needs of the biological community. I will explain how the twin revolutions in computation and biological science are combining to develop theoretical biology and will discuss the enormous impact this will have on science, medicine, and engineering.