ArticleFrontiers in plant science2016
Flux Balance Analysis of Plant Metabolism: The Effect of Biomass Composition and Model Structure on Model Predictions.
Article in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- MCC: automated mass and charge curation at the genome scale applied toMicrobiology spectrum · 2026Article
- A review of flavonoids at the crossroads of plant defense: integrating biotic and abiotic stress tolerance through AI- and CRISPR/Cas-guided metabolic reprogramming.Frontiers in plant science · 2026Review
- Multi-omics analysis of the metabolic and transcriptional regulatory mechanisms underlying strontium-induced anthocyanin accumulation in fresh purple maize.Frontiers in plant science · 2026Article
- Dynamic Constrained Allocation Flux Balance Analysis (dCAFBA).Methods in molecular biology (Clifton, N.J.) · 2026Article
- Unveiling organ-specific metabolism ofProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana.The New phytologist · 2025Article
- Biophysical modelling as a tool for advancing plant science and engineering.Frontiers in plant science · 2025Review
- The minimum energy required to build a cell.Scientific reports · 2024Article
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber.PLoS computational biology · 2023Article
- Genome-Scale Metabolic Reconstruction, Non-Targeted LC-QTOF-MS Based Metabolomics Data, and Evaluation of Anticancer Activity ofMetabolites · 2023Article
- Review
- Comparative plasma and urine metabolomics analysis of juvenile and adult canines.Frontiers in veterinary science · 2022Article
- Protocol for hybrid flux balance, statistical, and machine learning analysis of multi-omic data from the cyanobacteriumSTAR protocols · 2021Article
- Plant cell cultures as heterologous bio-factories for secondary metabolite production.Plant communications · 2021Review
- Thermodynamic Genome-Scale Metabolic Modeling of Metallodrug Resistance in Colorectal Cancer.Cancers · 2021Article
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.Advances in experimental medicine and biology · 2021Article
- A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria.iScience · 2020Article
- Flux balance analysis of cyanobacteria reveals selective use of photosynthetic electron transport components under different spectral light conditions.Photosynthesis research · 2020Article
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4 authors.
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Abstract
The biomass composition represented in constraint-based metabolic models is a key component for predicting cellular metabolism using flux balance analysis (FBA). Despite major advances in analytical technologies, it is often challenging to obtain a detailed composition of all major biomass components experimentally. Studies examining the influence of the biomass composition on the predictions of metabolic models have so far mostly been done on models of microorganisms. Little is known about the impact of varying biomass composition on flux prediction in FBA models of plants, whose metabolism is very versatile and complex because of the presence of multiple subcellular compartments. Also, the published metabolic models of plants differ in size and complexity. In this study, we examined the sensitivity of the predicted fluxes of plant metabolic models to biomass composition and model structure. These questions were addressed by evaluating the sensitivity of predictions of growth rates and central carbon metabolic fluxes to varying biomass compositions in three different genome-/large-scale metabolic models of Arabidopsis thaliana. Our results showed that fluxes through the central carbon metabolism were robust to changes in biomass composition. Nevertheless, comparisons between the predictions from three models using identical modeling constraints and objective function showed that model predictions were sensitive to the structure of the models, highlighting large discrepancies between the published models.
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