ArticleBMC bioinformatics2016
solveME: fast and reliable solution of nonlinear ME models.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- A systems-level atlas of carbon-response transcriptional states inProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Deciphering metabolic differentiation during Bacillus subtilis sporulation.Nature communications · 2025Article
- A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Integration of proteomic data with genome-scale metabolic models: A methodological overview.Protein science : a publication of the Protein Society · 2024Review
- Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective.Metabolites · 2024Review
- Predicting stress response and improved protein overproduction in Bacillus subtilis.NPJ systems biology and applications · 2022Article
- Review
- Genome-Scale Reconstruction of Microbial Dynamic Phenotype: Successes and Challenges.Microorganisms · 2021Review
- Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth.PLoS computational biology · 2021Article
- Emergence of diauxie as an optimal growth strategy under resource allocation constraints in cellular metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy.Scientific reports · 2021Article
- Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor.Cellular and molecular life sciences : CMLS · 2020Review
- Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli.PLoS computational biology · 2019Article
- Cellular responses to reactive oxygen species are predicted from molecular mechanisms.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- The genetic basis for adaptation of model-designed syntrophic co-cultures.PLoS computational biology · 2019Article
- DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression.BMC systems biology · 2019Article
- Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.Nature communications · 2018Article
- Identification of growth-coupled production strains considering protein costs and kinetic variability.Metabolic engineering communications · 2018Article
- Modeling the multi-scale mechanisms of macromolecular resource allocation.Current opinion in microbiology · 2018Review
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Authors and funding
6 authors.
Funding
Abstract
backgroundGenome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints.
resultsHere, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints.
conclusionsJust as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.