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  • 1
    Electronic Resource
    Electronic Resource
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 49 (1996), S. 364-376 
    ISSN: 0006-3592
    Keywords: Acinetobacter calcoaceticus ; bioprocess identification ; linear constrains ; error detection ; reconciliation ; metabolic flux ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Bioprocess identification starts with collection of process information. Usually there is a variety of information available, consisting of actual measurement data, historical data, empirical kinetic and yield correlations, and general knowledge available from literature. A central problem is to find out how the various pieces of information should be integrated. In addition, one should know how to deal with missing, inconsistent, or too inaccurate data. Recently, a general systematic method for dealing with these problems, based on conservation constraints, was published, and application shown to simple black box systems. In this article, the scope is generalized by including metabolic network data and dispersed process information of diverse type and nature, such as multiple sources of the value of one particular quantity, use of kinetic expressions, analytical problems, cometabolism or mixed substrate utilization, and chemical reactions. The alkalophilic bacterium Acinetobacter calcoaceticus is used as a model organism, growing on acetate and converting xylose into xylonolactone. It is shown that all relevant pieces of information can be straightforwardly and systematically treated, by considering them as constaints. In general, it is illustrated how the search for directed process improvements starts with an optimal selection of information sources, followed by an accurate analysis of possible metabolic bottlenecks. In this particular case it is shown that the yield of A. calcoaceticus on acetate at varying xylose/acetate feed ratios can be accurately predicted using dispersed process information. © 1996 John Wiley & Sons, Inc.
    Additional Material: 1 Ill.
    Type of Medium: Electronic Resource
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