Making Sense of Complexity Summary of the Workshop on Dynamical Modeling of Complex Biomedical Systems (2002) / Chapter Skim
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1 Introduction
1 Introduction
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While a range of challenges and approaches was discussed at the workshop, its overall theme was perhaps best summarized by discussant Jim Keener, of the University of Utah, who noted that what researchers in these areas are really trying to do is "make sense of complexity." The mathematical topics that play important roles in the quest include numerical analysis, scientific computing, statistics, optimization, and dynamical systems theory. Many biological systems are the result of interwoven interactions of simpler behaviors, with the result being a complex system that defies understanding through intuition or other simple means.
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Successful modeling starts with simple models to gain understanding. If the simple model succeeds somewhat in capturing the known or anticipated behavior, then work to refine it.
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In modeling very complex behaviors such as biomedical phenomena, these principles are the hallmark of good research.
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