Achievement

M-IOLITE is a computational suite for the efficient and automatic analysis of large metabolomic datasets, focusing on Gas Chromatography – Mass Spectrometry (GC-MS) metabolomics (Maga-Nteve & Klapa, 2018; Maga-Nteve, PhD Thesis, 2017; Maga-Nteve & Klapa, 2016). It streamlines untargeted metabolomic analysis and reduces complexity through the use of a friendly interface for storing, processing, validating and annotating data in the context of metabolic networks. M-IOLITE was reported as software for untargeted GC-MS-based metabolomics in the relevant full protocol, authored by our group in the Methods in Molecular Biology series (Papadimitropoulos et. al., 2018) and was cited in the review “New Tools in Metabolomics: 2016-2017” (Misra, Electrophoresis, 2018). It has been used in all published metabolomic studies of our laboratory. Its development is supported by the structural funding of ELIXIR-GR. It is available for free to all academic users upon request at http://miolite2.iceht.forth.gr.