DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations

Bioinformatics. 2021 Nov 5;37(21):3974-3975. doi: 10.1093/bioinformatics/btab622.


Motivation: Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account.

Results: We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations.

Availability and implementation: DEMETER and tutorials are freely available at

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Genome
  • Genomics
  • Metabolic Networks and Pathways*
  • Molecular Sequence Annotation
  • Software*