MetaBridge
MetaBridge compiles curated protein–metabolite interactions to enable network-based integration of metabolomics with other omics by focusing on direct protein interactors, including enzymes involved in biosynthesis and degradation.
Key Features:
- Curated protein–metabolite interactions: Compiles curated interactions between proteins and metabolites.
- Enzyme focus: Targets enzymes involved in both biosynthesis and degradation of metabolites.
- Protein interactor database: Provides a database of protein interactors that influence specific metabolite levels.
- Metabolic network support: Supports construction and analysis of metabolic networks linking metabolites and proteins.
- Omics integration and interoperability: Enables integration of metabolomics data with other omics datasets and interoperation with network analysis platforms such as NetworkAnalyst.ca.
Scientific Applications:
- Integrative metabolomics: Integrates metabolomics measurements with other omics to connect metabolites to molecular regulators.
- Systems biology: Facilitates systems-level analyses of metabolic pathways and network topology.
- Metabolic network analysis: Aids reconstruction and analysis of metabolic networks to interpret complex biological processes.
- Pathway and disease investigation: Provides molecular context for investigating metabolic pathways relevant to biological function and disease mechanisms.
Methodology:
Compiles curated protein–metabolite interaction data with emphasis on enzymes involved in biosynthesis and degradation, and supports construction and analysis of metabolic networks and integration with network analysis platforms such as NetworkAnalyst.ca.
Topics
Details
- License:
- GPL-3.0
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 6/1/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Hinshaw SJ, H Y Lee A, Gill EE, E W Hancock R. MetaBridge: enabling network-based integrative analysis via direct protein interactors of metabolites. Bioinformatics. 2018;34(18):3225-3227. doi:10.1093/bioinformatics/bty331. PMID:29688253.