Computational Mass Spectrometry (Dagstuhl Seminar 13491)

The last decade has brought tremendous technological advances in mass spectrometry, which in turn have enabled new applications of mass spectrometry in the life sciences. Proteomics, metabolomics, lipidomics, glycomics and related fields have gotten a massive boost, which also resulted in vastly increased amount of data produced and increased complexity of these data sets. An efficient and accurate analysis of these data sets has become the key bottleneck in the field. The seminar 'Computational Mass Spectrometry' brought together scientist from mass spetrometry and bioinformatics, from industry and academia to discuss the state of the art in computational mass spectrometry. The participants discussed a number of current topics, for example new and upcoming technologies, the challenges posed by new types of experiments, the challenges of the growing data volume ('big data'), or challenges for education in several working groups. The seminar reviewed the state of the art in computational mass spectrometry and summarized the upcoming challenges. The seminar also led to the creation of structures to support the computational mass spectrometry community (the formation of an ISCB Community of Interest and a HUPO subgroup on computational mass spectrometry). This community will also carry on with some of the efforts initiated during the seminar, in particular with the establishment of a computational mass spectrometry curriculum that was drafted in Dagstuhl.