A Protocol for the Automatic Construction of Highly Curated Genome-Scale Models of Human Metabolism

Igor Marin de Mas*, Helena Herand, Jorge Carrasco, Lars K. Nielsen, Pär I. Johansson

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Genome-scale metabolic models (GEMs) have emerged as a tool to understand human metabolism from a holistic perspective with high relevance in the study of many diseases and in the metabolic engineering of human cell lines. GEM building relies on either automated processes that lack manual refinement and result in inaccurate models or manual curation, which is a time-consuming process that limits the continuous update of reliable GEMs. Here, we present a novel algorithm-aided protocol that overcomes these limitations and facilitates the continuous updating of highly curated GEMs. The algorithm enables the automatic curation and/or expansion of existing GEMs or generates a highly curated metabolic network based on current information retrieved from multiple databases in real time. This tool was applied to the latest reconstruction of human metabolism (Human1), generating a series of the human GEMs that improve and expand the reference model and generating the most extensive and comprehensive general reconstruction of human metabolism to date. The tool presented here goes beyond the current state of the art and paves the way for the automatic reconstruction of a highly curated, up-to-date GEM with high potential in computational biology as well as in multiple fields of biological science where metabolism is relevant.
Original languageEnglish
Article number576
Issue number5
Number of pages19
Publication statusPublished - 2023


  • Genome-scale metabolic model
  • Human metabolism
  • Model construction
  • Constraints-based modeling


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