Supplementary dataset 11 - The effects of model complexity and size on metabolic flux distribution and control. Case study in Escherichia coli.

11th part of Supplementary dataset 1-15: contains populations of 50'000 control coefficients (Metabolic Control Analysis) for three models D1, D2, and D3 of different network size. These populations of control coefficients were used to study the effects of model complexity - in terms of network size - on the conclusions drawn from MCA. A metric for measuring the sensitivity of MCA control coefficients to these structural changes was proposed.

This work was supported by funding from the Ecole Polytechnique Fédérale de Lausanne (EPFL), the 2015/313 ERASysAPP RobustYeast Project funded through SystemsX.ch, the Swiss Initiative for Systems Biology evaluated by the Swiss National Science Foundation, and the Swiss National Science Foundation grant 315230_163423. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Related Organizations

École Polytechnique Fédérale de Lausanne EPFL
Switzerland

Keywords

Metabolic Networks, Metabolic Control Analysis, Kinetic Model, Model Complexity, Model Reduction

Impact byBIP!

	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).	0
	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.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average