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Frontiers of Engineering Reports on Leading-Edge Engineering from the 2001 NAE Symposium on Frontiers of Engineering (2002) / Chapter Skim
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Applying Simulation Technology to the Life Sciences
Pages 85-90

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From page 87...
... By contrast, the life sciences embrace the principles of observation, reductionism, and classical statistics. Clearly, engineers and life scientists have very different ways of looking at the world that present both opportunities and challenges for crossdisciplinary groups engaged in the simulation of biological systems.
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From page 88...
... Simulations of action potentials via fluctuations in ion channel function, which date back to the early 1950s, have yielded insights into cellular electrophysiology. The advent of molecular biology in the late 1980s provided entirely new technologies for perturbing and observing intracellular processes.
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From page 89...
... The physical sciences have benefited from both theoretical and empirical research made possible by the common language of mathematics since their inception. By contrast, the classical statistics used in the life sciences help researchers describe that certain phenomena occur but not how they occur.
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From page 90...
... All of our researchers, engineers and life scientists, scientific advisors, and software engineers have contributed to the advancement of our top-down simulation. THE FUTURE OF SIMULATION TECHNOLOGY IN THE LIFE SCIENCES Many projections have been made concerning the impact of research and health care in the postgenomic era, including predictions of innovative new therapies and personalized treatment regimens based on individual genetic factors.
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Key Terms

  • silico research
  • intracellular processes
  • data provide
  • empirical technologies
  • alternative hypotheses

  • component specifications
  • empirical research
  • internal states
  • classical statistics
  • help researchers

  • testing alternative
  • simulation goes
  • complex biological
  • empirical capabilities
  • blind trust

  • acute challenges
  • simple network
  • larger context
  • larger network
  • developing complex

  • simulations typically
  • including cardiac
  • formal hypotheses
  • pharmaceutical partners
  • genetic factors

  • desired behavior
  • facing acute
  • tissue level
  • integrated biological
  • simulations help


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