Frontiers of Engineering Reports on Leading-Edge Engineering From the 2000 NAE Symposium on Frontiers in Engineering (2001) / Chapter Skim
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Bioengineering for the Science and Technology of Biological Systems
Bioengineering for the Science and Technology of Biological Systems
Pages 62-74
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From page 62... ...
Molecular biology, on the one hand, ultimately offers reductionist knowledge concerning molecular mechanisms governing functions at all higher hierarchical levels: cell, tissue, organ, and organism. Genomics, on the other hand, at least promises global knowledge concerning relationships of genetically encoded information and operation of the physiological system for which it serves as the core program.
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From page 63... ...
Messenger RNA levels for even the full transcriptome, likewise, do not adequately represent the levels of the proteins they spawn. Researchers have demonstrated mathematically, for instance, that the dynamic behavior of a gene regulation network may not be properly predicted solely from gene expression data (Hatzimanikatis et al., 1999a)
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From page 64... ...
FIGURE 1 Illustration of an engineering perspective on biological systems as a dynamic function dependent on component properties. What engineers generally bring to the research table is a predilection to analyze a complicated system in terms of principles useful for manipulating that system, with the goal of making it operate in some intended fashion (see Figure 1~.
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From page 65... ...
For instance, the Asthma PhysioLab model attempts to account for how the resistance to air flow in the lungs is governed by cell-level functions (e.g., airway smooth muscle cell contractility, airway epithelial cell permeability, white blood cell accumulation in tissues, and secretion of inflammatory mediators) , which are, in turn, regulated by cytokine/receptor interactions and consequent intracellular signaling pathways (see Figure 2a)
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From page 67... ...
. However, rather than rushing headlong into writing differential equations for all components and interactions, Tyson's and Bailey's groups at Virginia Polytechnic Institute and State Univer
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From page 68... ...
SOURCE: Reprinted with permission from the American Society for Cell Biology (Kohn, 2000~.
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From page 69... ...
. Again, one can aim for construction of dynamic systems behavior versus parameter relationships, such as a bifurcation diagram for understanding and predicting conditions under which cells will progress through a DNA synthesis checkpoint or not (see Figure 3c)
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From page 70... ...
It is conceivable that much of the uncertainty regarding quantitative parameter values might, in fact, be rendered less problematic by this concept of functional and control modules, because their dynamic operation may turn out to be surprisingly insensitive to specific parameter values (von Dassow et al., 2000~. This idea will be very interesting to examine with emerging powerful genetic (Rao and Verkman, 2000)
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From page 71... ...
. While at first glance this might seem to be a step backward, the physicochem~cal detail has not disappeared; rather, it is ultimately responsible for the dynamic behavior, including the quantitative parameter values, so the feedback control loop could be replaced by the detailed subsystem whenever the complete set of information becomes available.
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From page 72... ...
_ —y(t) FIGURE 4c Schematic of feedback control module, which can generate the dynamic signal behavior shown in Figure 4b.
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From page 73... ...
Out of hundreds of putative death-activating and survival-protective genes and dozens of protein-based physicochemical kinetic and transport processes we have selected a subset for microarray expression and proteomic experimental measurement following challenge by a matrix of input stimuli. The question posed is whether we can determine a signal processing algorithm utilized by the cells to make their decision based on information flows through key regulatory networks (e.g., Arkin and Ross, 1994~.
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From page 74... ...
2000. Robust perfect adaptation in bacterial chemotaxis through integral feedback control.
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