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What can metabolomics learn from genomics and proteomics?
1Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Japan. arita@k.u-tokyo.ac.jp
Current Opinion in Biotechnology
|October 24, 2009
Summary
Metabolomics is gaining scientific acceptance, but needs robust web infrastructure. Public data servers and analysis tools are key to its widespread adoption and integration with other research fields.
Area of Science:
- Biochemistry
- Bioinformatics
- Systems Biology
Background:
- Metabolomics is emerging as a scientific discipline but lacks the widespread acceptance of genomics and proteomics.
- The scientific community's validation of metabolomics is crucial for its growth and impact.
Purpose of the Study:
- To explore the factors influencing the scientific acceptance of metabolomics.
- To identify strategies for establishing metabolomics as a fundamental data-driven science.
Main Methods:
- Analysis of the role of web infrastructure in scientific community growth.
- Evaluation of public servers, data formats, and analysis tools for metabolomics data.
- Assessment of the potential for metabolomics to unite diverse research disciplines.
Main Results:
- Web infrastructure, including public data servers and analysis tools, is critical for metabolomics.
- Standardized formats and interpretation guidelines accelerate scientific adoption.
- Connectivity between data and analytical tools fosters interdisciplinary research.
Conclusions:
- The legitimization of metabolomics hinges on community size and engagement.
- A robust web infrastructure can drive the social epidemic needed for metabolomics acceptance.
- Metabolomics has the potential to become a unifying, data-driven science.
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