Chemistry project wins prize for ‘best automated metabolite prediction tool’
17 Sep 2014 - 2 min
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Mass spectrometry is an essential analytical technique in a wide range of scientific disciplines. It enables scientists to obtain a comprehensive profile of the (bio)molecules present in complex biological samples. As mass spectrometers rapidly gain speed, sensitivity and accuracy, the data they produce is growing exponentially. A critical step in the interpretation of this data is the elucidation of the chemical structures of large numbers of detected, yet unknown compounds. As manual interpretation requires substantial time and effort by dedicated human experts, automation of this step is crucial to be able fully exploit the big datasets generated by new generation mass spectrometers.
The CASMI (Critical Assessment of Small Molecule Identification) 2013 contest challenged scientists worldwide to interpret mass spectral data from 16 molecules. Whereas manual analysis by a participating team of experts resulted in most correct solutions, the best result among the automatic methods, obtained with unequaled computational efficiency, were provided by the team of Lars Ridder (WUR), Justin van der Hooft (University of Glasgow) en Stefan Verhoeven (NLeSC) on the basis of MAGMa. The ongoing development of MAGMa at Wageningen University and the Netherlands eScience Center will cause a breakthrough in routine practices for large scale small (bio)molecule profiling in a range of scientific disciplines.