g2f as a Novel Tool to Find and Fill Gaps in Metabolic Networks

During the building of a genome-scale metabolic model, there are several dead-end metabo lites and substrates which cannot be imported, produced, nor used by any reaction incorporated in the network. The presence of these dead-end metabolites can block out the net flux of the objective function when it is evaluated through Flux Balance Analysis (FBA), and when it is not blocked, bias in the biological conclusions increase. In this aspect, the refinement to restore the connectivity of the network can be carried out manually or using computational algorithms. The g2f package was designed as a tool to find the gaps from dead-end metabolites and fill them from the stoichiometric reactions of a reference, filtering candidate reactions using a weighting function. Additionally, this algorithm allows downloading all the sets of gene-associated stoichiometric reactions for a specific organism from the KEGG database. Our package is compatible with both 4.0.0 and 3.6.0 R versions.

Daniel Osorio , Kelly Botero , Andrés Pinzón Velasco , Nicolás Mendoza-Mejía , Felipe Rojas- Rodríguez , George Barreto , Janneth González
2021-07-15

CRAN packages used

g2f, sybil

CRAN Task Views implied by cited packages

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Osorio, et al., "g2f as a Novel Tool to Find and Fill Gaps in Metabolic Networks", The R Journal, 2021

BibTeX citation

@article{RJ-2021-064,
  author = {Osorio, Daniel and Botero, Kelly and Velasco, Andrés Pinzón and Mendoza-Mejía, Nicolás and Rodríguez, Felipe Rojas- and Barreto, George and González, Janneth},
  title = {g2f as a Novel Tool to Find and Fill Gaps in Metabolic Networks},
  journal = {The R Journal},
  year = {2021},
  note = {https://doi.org/10.32614/RJ-2021-064},
  doi = {10.32614/RJ-2021-064},
  volume = {13},
  issue = {2},
  issn = {2073-4859},
  pages = {28-37}
}