COBRAxy: constraint-based metabolic modeling in Galaxy.
Where this comes from
- Record sourced from PubMed, PMID 41423731.
- Also identified by DOI 10.1093/bioinformatics/btaf670 and PMC identifier 12926780.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Metabolic network modeling is essential for understanding metabolic shifts occurring in complex physio-pathological processes. Currently, constraint-based modeling frameworks for metabolic networks primarily rely on Python or MATLAB libraries, requiring some coding skills. In contrast, more user-friendly tools lack essential features such as flux sampling or transcriptomic data integration. We introduce COBRAxy, a Python-based tool suite integrated into the Galaxy Project. COBRAxy enables constraint-based modeling and sampling techniques, allowing users to compute metabolic flux distributions for multiple biological samples. The tool also enables the integration of medium composition information to refine flux predictions. Additionally, COBRAxy provides a user-friendly interface for visualizing significant flux differences between populations on an enriched metabolic map. This extension provides a comprehensive and accessible framework for advanced metabolic analysis, enabling researchers without extensive programming expertise to explore complex metabolic processes. COBRAxy is available in the Galaxy ToolShed https://toolshed.g2.bx.psu.edu/view/bimib/cobraxy/9f78303dbd88.
Medical subject headings
- Software
- Metabolic Networks and Pathways
- Models, Biological
- Computational Biology