ScyNet: Visualizing interactions in community metabolic models

Michael Predl; Kilian Gandolf; Michael Hofer; Thomas Rattei

doi:10.1093/bioadv/vbae104

ScyNet: Visualizing interactions in community metabolic models

Bioinform Adv. 2024 Jul 17;4(1):vbae104. doi: 10.1093/bioadv/vbae104. eCollection 2024.

Authors

Michael Predl^{1

2}, Kilian Gandolf¹, Michael Hofer¹, Thomas Rattei^{1

2}

Affiliations

¹ Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna 1030, Austria.
² Doctoral School in Microbiology and Environmental Science, University of Vienna, Vienna 1030, Austria.

Abstract

Motivation: Genome-scale community metabolic models are used to gain mechanistic insights into interactions between community members. However, existing tools for visualizing metabolic models only cater to the needs of single organism models.

Results: ScyNet is a Cytoscape app for visualizing community metabolic models, generating networks with reduced complexity by focusing on interactions between community members. ScyNet can incorporate the state of a metabolic model via fluxes or flux ranges, which is shown in a previously published simplified cystic fibrosis airway community model.

Availability and implementation: ScyNet is freely available under an MIT licence and can be retrieved via the Cytoscape App Store (apps.cytoscape.org/apps/scynet). The source code is available at Github (github.com/univieCUBE/ScyNet).