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We represent a community with a shared interest in data analysis using the population approach.


2003
   Verona, Italy

Developing Integrated Cell Systems

James B. Bassingthwaighte

Bioengineering, University of Washington, Seattle WA

The strategies and techniques for developing integrated frameworks for systems of molecules, cells, tissues, and organs are complex. The natural beginnings of designs for systematic approaches are usually framed as diagrams of relationships; biochemical charts are a prime example. Physiological connectivity diagrams are often less precise, in that the nature of the relationships is not immediately so apparent as in biochemical systems with enzyme-facilitated reactions. At the subcellular level, functional descriptions for the behavior of enzymes, transporters, pumps, channels and receptors can usually be described in kinetic and biophysical terms and translated into quantitative relationships using ordinary differential equations, even while accounting at least crudely for subcellular microcompartmentation. This level of simplicity begins to fail even at the single cell level when spatial variations in concentrations must be accounted for in the kinetics, as occurs with Ca2+ cycling in excitable cells. Within an organ, with its multiple cell types, the normal spatial heterogeneity of blood flows, metabolic rates, and tissue contractile or excretory or secretory functions it is difficult to consider organ function in terms of the functions of a single cell type, but in certain cases it can work to describe organ function. e.g. for an oversimplified cardiac contraction. In reality intercellular solute flow and signaling must be accounted for. One builds the more complex systems out of modules or components. It turns out that it is technically easier to build multiorgan models, where the organs have relatively loose connections between them, than it is to build comprehensive cell models in which reactions amongst components are tightly coupled. For these reason, building hierarchical models composed of pyramids of components requires compromises in order to be computable. Inevitably this means that the highest level models cannot be based on fundamental thermodynamic and molecular considerations, and in effect cannot be as adaptable as the real system.(Research supported by NIH/NIBIB.)



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