ArticlePLoS computational biology2019
Cellular determinants of metabolite concentration ranges.
Article in PLoS computational biology, 2019. 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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4 citing papers in PubMed.
- Integration of biological and information technologies to enhance plant autoluminescence.The Plant cell · 2024Article
- Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth.Nature communications · 2020Article
- Flux-based hierarchical organization of Escherichia coli's metabolic network.PLoS computational biology · 2020Article
- Computational Approaches to Design and Test Plant Synthetic Metabolic Pathways.Plant physiology · 2019Review
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4 authors.
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Abstract
Cellular functions are shaped by reaction networks whose dynamics are determined by the concentrations of underlying components. However, cellular mechanisms ensuring that a component's concentration resides in a given range remain elusive. We present network properties which suffice to identify components whose concentration ranges can be efficiently computed in mass-action metabolic networks. We show that the derived ranges are in excellent agreement with simulations from a detailed kinetic metabolic model of Escherichia coli. We demonstrate that the approach can be used with genome-scale metabolic models to arrive at predictions concordant with measurements from Escherichia coli under different growth scenarios. By application to 14 genome-scale metabolic models from diverse species, our approach specifies the cellular determinants of concentration ranges that can be effectively employed to make predictions for a variety of biotechnological and medical applications.
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