Metabolomics Data Analysis – Turning complex metabolomics data into meaningful results

Turning complex metabolomics data into meaningful results

Metabolomics analyses typically involve very large sample sets, resulting in the production of complex data outputs. To fully extrapolate meaningful biological information, large sample sets must be run to obtain statistical significance. Metabolomics data analysis typically consists of feature extraction, quantitation, statistical analysis and compound identification.

The Thermo Scientific metabolomics software suite is specifically designed to mine complex HRAM Orbitrap data, converting large datasets into meaningful results.

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