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Following in the steps of high-throughput sequencing, mass spectrometry (MS) has become established as a key analytical technique for large-scale studies of complex biological mixtures. MS-based experiments generate datasets of increasing complexity and size, and the rate of production of these datasets has exceeded Moore's law. In recent years we have witnessed the growth of computational approaches to coping with this data deluge. The seminar 'Computational Mass Spectrometry' brought togetherdoi:10.4230/dagrep.5.8.9 dblp:journals/dagstuhl-reports/AebersoldKV15 fatcat:2zgxjmy3fbfw3fvrjrekkpjlle