PT  - JOURNAL ARTICLE
AU  - Archana Hari
AU  - Daniel Lobo
TI  - <em>mergem</em>: merging and comparing genome-scale metabolic models using universal identifiers
AID  - 10.1101/2022.07.14.499633
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.07.14.499633
4099  - http://biorxiv.org/content/early/2022/08/11/2022.07.14.499633.short
4100  - http://biorxiv.org/content/early/2022/08/11/2022.07.14.499633.full
AB  - Numerous methods exist to produce and refine draft genome-scale metabolic models. However, there is a lack of automated tools that can integrate these drafts into a curated single comprehensive model. In addition, computing and visualizing metabolic differences and similarities, including reconstructions using incompatible identifiers, is a current challenge. Here we present mergem, a novel method to compare and merge two or more metabolic models using a universal metabolic identifier mapping system constructed from multiple metabolic databases. mergem is implemented as a Python package and on the web-application Fluxer, which allows simulating and comparing multiple models with different interactive flux graphs.Competing Interest StatementThe authors have declared no competing interest.