Biologic Computational

Since the time of Newton, a key scientific strategy has been to understand physical systems based on their representation in terms of the smallest possible subsystem (i.e., model) that captures the important mechanistic interactions. The influence of gravity in maintaining the earth’s orbit about the sun is satisfactorily explained byanalyzing the equations of motion representing a universe consisting of two massive
bodies; a complete mathematical analysis of the three-body problem remains out of reach. Living biological systems consist of not two, or even two hundred interacting components. Analysis, prediction, and rational manipulation of cellular function requires a mechanistic understanding of physical systems of unimaginable complexity. Thus the computer is an essential tool in helping us to analyze and simulate living systems.

The term computational biology has emerged to describe theoretical and computer-aided analysis and prediction of biological behaviors.Yet while theterminology may be new, the practice of computational biology is not In 1919 August Krogh and Agner Erlang established one of the first mathematical models of a living system used to predict the oxygen distribution around a capillary based on a model formulation that is still in use today [136, 157]. It has been over five decades since Alan Hodgkin and Andrew Huxley published their work using computational modeling to characterize the electrophysiological function of the squid giant axon Current work in computational biology takes advantage of computational resources that are well beyond anything that was available to Krogh or Hodgkin and Huxley. Yet in terms of clarity, precision, and insight, the work of these Nobel Prize winning physiologists continues to set the standard for the field.