Systems Biology, Integrative Biology, Predictive Biology

The pursuit of science is based on empiricism enabled by advancing technologies. Theories then emerge that unify our understanding of natural order. The trinity of experimentation, theory, and technology that underlies the scientific method cannot be placed into a hierarchy of importance. Theoretical fields quickly lose substance in the absence of robust experimentation, and theoretical conundrums cannot be resolved without experimentation using advanced technologies. Physics is perhaps the most mature of the experimental sciences in exploiting the interface between theory, experimentation, and technology. Quantum and relativity theories revolutionized physics and engineering, but high-energy physics is a discipline made possible by the technology of the linear accelerator. The advantage of physics over other experimental sciences is the ability to use first principles to calculate more complex models of the physical world. These models are then used to predict unforeseen physical events. Fundamental to this is the ability to precisely quantify physical observations and to render them mathematically transformable. This progression from observation, to theory, to prediction has been the driving force in humanity’s fascination with science. Not only do we have an inherent appetite for knowledge that motivates us to explore, but we also have a desire to extract reason from perceived chaos in order to construct models that can predict our future. In this past century, biology has transformed from a primarily empiric and observational field to one based on fundamental principles. The foundations for this change may be attributed to a great degree to the discovery of the true structure of DNA, and followed by the recent ability to sequence entire genomes. We are now poised to advance further into predictive theory with the new discipline of systems biology. Systems biology can be different things to different people, but there is a common understanding that this discipline seeks to explain biologic phenomenon, not on a gene-by-gene basis, but through the net interactions of all cellular and biochemical components within a cell or organism. Operationally, systems biology requires the ability to digitalize biological output so that it can be computed, the computational power to analyze comprehensive and massive datasets, and the capacity to integrate heterogeneous data into a usable knowledge format. Thus, systems biology can be described as “integrative biology” with the ultimate goal of being able to predict de novo biological outcomes given the