Library

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Electronic Resource
    Electronic Resource
    Derivation of kinetic equations for growth on single substrates based on general properties of a simple metabolic network (1995)
    s.l. : American Chemical Society
    Biotechnology progress 11 (1995), S. 712-716 
    Details
    ISSN: 1520-6033
    Source: ACS Legacy Archives
    Topics: Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1021/bp00036a018
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 2
    Electronic Resource
    Electronic Resource
    Linear constraint relations in biochemical reaction systems: II. Diagnosis and estimation of gross errors (1994)
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 43 (1994), S. 11-20 
    Details
    ISSN: 0006-3592
    Keywords: conservation equations ; linear constraints ; data reconciliation ; balancing technique ; gross error detection ; error diagnosis ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Conservation equations derived from elemental balances, heat balances, and metabolic stoichiometry, can be used to constrain the values of conversion rates of relevant components. In the present work, their use will be discussed for detection and localization of significant errors of the following types: 1.At least one of the primary measurements has a significant error (gross measurement error).2.The system definition is incorrect: a component a.is not included in the system description.b.has a composition different from that specified.3.The specified variances are too small, resulting in a too-sensitive test.The error diagnosis technique presented here, is based on the following: given the conservation equations, for each set of measured rates, a vector of residuals of these equations can be constructed, of which the direction is related to the error source, as its length is a measure of the error size. The similarity of the directions of such a residual vector and certain compare vectors, each corresponding to a specific error source, is considered in a statistical test. If two compare vectors that result from different error sources have (almost) the same direction, errors of these types cannot be distinguished from each other. For each possible error in the primary measurements of flows and concentrations, the compare vector can be constructed a priori, thus allowing analysis beforehand, which errors can be observed. Therefore, the detectability of certain errors likely to occur can be insured by selecting a proper measurement set. The possibility of performing this analysis before experiments are carried out is an important advantage, providing a profound understanding of the detectability of errors. The characteristics of the method with respect to diagnosis of simultaneous errors and error size estimation are discussed and compared to those of the serial elimination method and the serial compensation strategy, published elsewhere. © 1994 John Wiley & Sons, Inc.
    Additional Material: 4 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/bit.260430104
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    Linear constrain relations in biochemical reaction systems III. Sequential application of data reconciliation for sensitive detection of systematic errors (1994)
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 44 (1994), S. 781-791 
    Details
    ISSN: 0006-3592
    Keywords: error diagnosis ; filtering technique ; data reconciliation ; measurement error detection ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: This article presents a method to test the presence of relatively small systematic measurement errors; e.g., those caused by inaccurate calibration or sensor drift. To do this, primary measurements - flow rates and concentrations - are first translated into observed conversions, which should satisfy several constraints, like the laws of conservation of chemical elements. This study considers three objectives: 1.Modification of the commonly used balancing technique to improve error sensitivity to be able to detect small systematic errors. To this end, the balancing technique is applied sequentially in time.2.Extension of the method to enable direct diagnosis of errors in the primary measurements instead of diagnosing errors in the observed conversions. This was achieved by analyzing how individual errors in the primary measurements are expressed in the residual vector.3.Derivation of a new systematic method to quantitatively determine the sensitivity of the error, is that error size at which the expected value of the chisquare test function equals its critical value.The method is applied to industrial data demonstrating the effectiveness of the approach. It was shown that, for most possible error sources, a systematic errors of 2% to 5% could be detected. In given application, the variation of the N-content of biomass was appointed to be the cause of errors. © 1994 John Wiley & Sons, Inc.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/bit.260440703
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 4
    Electronic Resource
    Electronic Resource
    Linear constraint relations in biochemical reaction systems: I. Classification of the calculability and the balanceability of conversion rates (1994)
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 43 (1994), S. 3-10 
    Details
    ISSN: 0006-3592
    Keywords: data reconciliation ; balancing ; classification ; observability ; redundancy ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Measurements provide the basis for process monitoring and control as well as for model development and validation. Systematic approaches to increase the accuracy and credibility of the empirical data set are therefore of great value. In (bio)chemical conversions, linear conservation relations such as the balance equations for charge, enthalpy, and/or chemical elements, can be employed to relate conversion rates. In a pactical situation, some of these rates will be measured (in effect, be calculated directly from primary measurements of, e.g., concentrations and flow rates), as others can or cannot be calculated from the measured ones. When certain measured rates can also be calculated from other measured rates, the set of equations, the accuracy and credibility of the measured rates can indeed be improved by, respectively, balancing and gross error diagnosis. The balanced conversion rates are more accurate, and form a consistent set of data, which is more suitable for further application (e.g., to calculate nonmeasured rates) than the raw measurements. Such an approach has drawn attention in previous studies. The current study deals mainly with the problem of mathematically classifying the conversion rates into balanceable and calculable rates, given the subset of measured rates. The significance of this problem is illustrated with some examples. It is shown that a simple matrix equation can be derived that contains the vector of measured conversion rates and the redundancy matrix R. Matrix R plays a predominant role in the classification problem. In supplementary articles, significance of the redundancy matrix R for an improved gross error diagnosis approach will be shown. In addition, efficient equations have been derived to calculate the balanceable and/or calculable rates. The method is completely based on matrix algebra (principally different from the graph-theoretical approach), and it is easily implemented into a computer program. © 1994 John Wiley & Sons, Inc.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/bit.260430103
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 5
    Electronic Resource
    Electronic Resource
    Classification, error detection, and reconciliation of process information in complex biochemical systems (1996)
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 49 (1996), S. 364-376 
    Details
    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
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
  • 6
    Electronic Resource
    Electronic Resource
    Kinetic analysis of enzymatic chiral resolution by progress curve evaluation (1994)
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 43 (1994), S. 411-422 
    Details
    ISSN: 0006-3592
    Keywords: enzyme kinetics ; progress curve ; enantioselectivity ; covariance ; kinetic resolution ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: The present study deals with kinetic modeling of enzyme-catalyzed reactions by integral progress curve analysis, and shows how to apply this technique to kinetic resolution of enantiomers. It is shown that kinetic parameters for both enantiomers and the enantioselectivity of the enzyme may be obtained from the progress curve measurement of a racemate only.A parameter estimation procedure has been established and it is shown that the covariance matrix of the obtained parameters is a useful statistical tool in the selection and verification of the model structure. Standard deviations calculated from this matrix have shown that progress curve analysis yields parameter values with high accuracies.Potential sources of systematic errors in (multiple) progress curve analysis are addressed in this article. Amongst these, the following needed to be dealt with: (1) the true initial substrate concentrations were obtained from the final amount of product experimentally measured (mass balancing); (2) systematic errors in the initial enzyme concentration were corrected by incorporating this variable in the fitting procedure as an extra parameter per curve; and (3) enzyme inactivation is included in the model and a first-order inactivation constant is determined.Experimental verification was carried out by continuous monitoring of the hydrolysis of ethyl 2-chloropropionate by carboxylesterase NP and the α-chymotrypsin-catalyzed hydrolysis of benzoylalanine mathyl ester in a pH-stat system. Kinetic parameter values were obtained with high accuracies and model predictions were in good agreement with independent measurements of enantiomeric excess values or literature data. © 1994 John Wiley & Sons, Inc.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/bit.260430509
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...