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Biotechnology and Bioengineering
Article . 1978 . Peer-reviewed
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Mathematical modeling of lag phases in microbial growth

Authors: Barford, John Patrick; Pamment, Neville B.; Hall, R.J.;

Mathematical modeling of lag phases in microbial growth

Abstract

AbstractThis paper describes a mathematical model of the lag phases of Saccharomyces cerevisiae that incorporates the basic concepts previously presented in a two‐stage deterministic model for the growth of this organism under conditions of oxygen excess with a sugar as the growth‐limiting substrate. The model structure was suggested by an extensive investigation of the causes of the lag phases of S. cerevisiae which found that, in contrast to the traditionally accepted trends, the length of the lag phase was not inoculum‐size dependent. This was consistent with other previously published work which suggested that a major factor in the length of the lag phases in S. cerevisiae was the need to synthesize adequate levels of glycolytic and respiratory enzymes. These suggestions were confirmed experimentally with lag‐age data. Based on this conclusion a mathematical model was developed incorporating a description of the levels of glycolytic and respiratory enzymes and their effect on the growth rate and metabolism. This model was tested experimentally and the initial results indicate indicate that many aspects of the lag phase of this organism may be described mathematically. The experimental findings further support the concept of primary regulatory control proposed by Bijkerk and Hall.

Country
China (People's Republic of)
Related Organizations
Keywords

612, Saccharomyces cerevisiae, Glycolysis, Models, Biological, Mathematics, NADP

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
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