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Bioinformatic tools are required to carry out essential functions such as statistical analyses and database functionalities. Now, they are also needed for one of the most difficult tasks, helping researchers decide which metabolites are the most biologically meaningful. This can be achieved through aiding the identification process, reducing feature redundancy, putting forward better candidates for tandem mass spectrometry (MS/MS), speeding up or automating the workflow, deconvolving the feature list through meta-analysis or multigroup analysis, or using stable isotopes and pathway mapping. This review thus focuses on the most recent and innovative bioinformatic advancements for identifying metabolites. A primary objective of metabolomics beyond biomarker discovery is to identify the most meaningful metabolites that correlate with disease pathogenesis or other perturbations of metabolism. Metabolites play …