Computational Approaches to Metabolomics
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Automatic Annotation of Metabolomic Mass Spectra
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Unbiased metabolomic surveys are used for physiological, clinical
and genomic studies to infer genotype-phenotype relationships. Long term reusability
of metabolomic data needs both correct metabolite annotations and
consistent biological classifications. We have developed a system that combines
mass spectrometric and biological metadata to achieve this goal. First, an XMLbased
LIMS system enables entering biological metadata for steering laboratory
workflows by generating ‘classes’ that reflect experimental designs. After data
acquisition, a relational database system (BinBase) is employed for automated
metabolite annotation. It consists of a manifold filtering algorithm for matching
and generating database objects by utilizing mass spectral metadata such as
‘retention index’, ‘purity’, ‘signal/noise’, and the biological information class.
Once annotations and quantitations are complete for a specific larger
experiment, this information is fed back into the LIMS system to notify
supervisors and users. Eventually, qualitative and quantitative results are
released to the public for downloads or complex queries.
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Created by
scholz
Last modified 2005-09-22 03:14 PM
Last modified 2005-09-22 03:14 PM
