Neuropeptides play an important role in signalling between neurons and are known to be involved in processes such as addiction and depression . Applying tandem mass spectrometry, these neuropeptides can be identified and quantified, and related to the process of interest ,. Opposed to regular proteins, these peptides undergo several transformations from their so-called precursor protein to their functional neuropeptides , and can therefore not be readily predicted from their corresponding genes. This poses a problem for conventional database search algorithms (e.g. MSGF+  or Tide ), as the number of hypotheses grows exponentially. We have previously developed a clustering algorithm, MaRaCluster , which could help in reducing the number of spectra that need to be searched, as well as discover frequently occurring unidentified spectra. The former helps in reducing the number of hypothesis directly, while the latter opens up the possibility of using search algorithms that employ experimental spectra (e.g. SpectraST  or BiblioSpec ), instead of theoretical spectra.
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