Bioinformatics Tools for the Interpretation of Metabolomics Data

Purpose of Review: Metabolomics is a rapidly evolving field that generates large and complex datasets. Bioinformatics becomes critical towards the extraction of meaningful biological information. In this article, we briefly review computational approaches that have been well accepted in the field, and discuss the development of new methods and tools to interpret metabolomics data. Recent Findings: Significant progress has been made in computational metabolomics over the past years. This includes methods that are used to preprocess data generated by instruments, to annotate metabolites, to carry out statistical analyses, to identify perturbed metabolic pathways, and to integrate metabolomics with other omics data. Each of these topics is discussed in respective sections of this review. Summary: Bioinformatics tools used for metabolomics remain a highly active research area. An ecosystem is emerging with software libraries, standalone tools, and web-based tools and services. While some require bioinformatics training, many of them are user friendly and easily accessible. Much further development is still needed to serve the metabolomics field and its applications.