ArticlePLoS computational biology2013
Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 20 citations in OpenAlex.
- Discovery and cultivation of prokaryotic taxa in the age of metagenomics and artificial intelligence.The ISME journal · 2025Article
- Characterization of serum metabolome and respiratory microbiota in children with influenza A virus infection.Frontiers in cellular and infection microbiology · 2024Article
- Genome-scale metabolic modeling reveals key features of a minimal gene set.Molecular systems biology · 2021Article
- Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate.Biotechnology and bioengineering · 2017Article
- Synthetic biology advances for pharmaceutical production.Current opinion in biotechnology · 2015Review
- Hydrogen peroxide production from glycerol metabolism is dispensable for virulence of Mycoplasma gallisepticum in the tracheas of chickens.Infection and immunity · 2014Article
- Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe.Journal of bacteriology · 2014Article
- Promise and reality in the expanding field of network interaction analysis: metabolic networks.Bioinformatics and biology insights · 2014Article
- Comparative Metabolomics ofmSystemsArticle
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.
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Registered trials
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.