ArticleBMC systems biology2011
Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger.
Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 15 citations in OpenAlex.
- Review
- Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger.BMC systems biology · 2016Article
- New coronavirus outbreak. Lessons learned from the severe acute respiratory syndrome epidemic.Epidemiology and infection · 2015Article
- Deciphering transcriptional regulatory mechanisms associated with hemicellulose degradation in Neurospora crassa.Eukaryotic cell · 2012Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysis is performed. The activating, repressive feedback, and the combined effect of the two feedbacks on the network behavior are analyzed.
resultsSimulation and systems analysis showed significant influence of activating and repressing feedback on metabolite expression profiles. The dynamics of the D-xylose input function has an important effect on the profiles of the individual metabolite concentrations. Variation of the time delay in the feedback loop has no significant effect on the pattern of the response. The stability and existence of oscillatory behavior depends on which proteins are involved in the feedback loop.
conclusionsThe dynamics in the regulation properties of the network are dictated mainly by the transcription and translation degradation rate parameters, and by the D-xylose consumption profile. This holds true with and without feedback in the network. Feedback was found to significantly influence the expression dynamics of genes and proteins. Feedback increases the metabolite abundance, changes the steady state values, alters the time trajectories and affects the response oscillatory behavior and stability conditions. The modeling approach provides insight into network behavioral dynamics particularly for small-sized networks. The analysis of the network dynamics has provided useful information for experimental design for future in vitro experimental work.
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