Strides in the technology of systems physiology and the art of testing complex hypotheses.

Abstract

Scientific understanding in physics or physiology is based on models or theories devised to describe what is known, within the limits imposed by observation error. Carefully integrated models can be used for prediction, and the inferences assessed via further experiments designed to test the adequacy of the theory summarizing the state of knowledge. This is the systems approach, the basis of theoretical physiology; the models, like those of theoretical physics, should be firmly based on fundamental reproducible observations of a physical or chemical nature, held together with the principles of mathematics, logic, and the conservation of mass and energy. Modern computing power is such that comprehensive models can now be constructed and tested. For this approach data sets should include as many simultaneously obtained items of information of differing sorts as possible to reduce the degrees of freedom in fitting models to data. By taking advantage of large memories and rapid computation, modular construction techniques permit the formulation of multimodels covering more than a single hierarchical level, and thereby allow the investigator to understand the effects of controllers at the molecular level on overall cell or organism behavior. How does this influence the research and teaching practices of physiology? Because the computer also allows a new type of collaboration involving the networking of ideas, data bases, analytical techniques, and experiment designing, investigators in geographically distributed individual laboratories can plan, work, and analyze in concert. The prediction from this socioscientific model is therefore that networked computer-based modeling will serve to coalesce the ideas and observations of enlarging groups of investigators.