MeMo: A Model for Metabolomic Data Management
Author Information
Author(s): Spasić Irena, Dunn Warwick B, Velarde Giles, Tseng Andy, Jenkins Helen, Hardy Nigel, Oliver Stephen G, Kell Douglas B
Primary Institution: The University of Manchester
Hypothesis
MeMo aims to provide a structured and efficient way to manage large-scale metabolomic data for functional genomics.
Conclusion
MeMo effectively integrates relational database technology with XML to manage complex metabolomic data.
Supporting Evidence
- MeMo has been implemented as a relational database to handle metabolomic data efficiently.
- The model supports integration with other databases through ontological annotation.
- MeMo is designed to be extensible to accommodate new experimental techniques.
Takeaway
MeMo is like a smart filing system for scientists that helps them organize and understand a lot of data about tiny molecules in living things.
Methodology
MeMo combines SQL and XML technologies to create a relational database for metabolomic data management.
Limitations
The model may not cover all aspects of metabolomics and relies on existing standards that are still evolving.
Digital Object Identifier (DOI)
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