Several large proteomics spectral libraries exist as well. These include peptide MS/MS spectral libraries for multiple organisms (human, mouse, rat, yeast, etc.) from NIST (), the ProteomeTools project of synthetic human peptide MS/MS spectra , and the MassIVE Knowledge Base (MassIVE-KB) of the human proteome (M. . Different strategies for compiling spectral libraries are exemplified by the ProteomeTools and MassIVE-KB peptide spectral libraries (M. . On the one hand, ProteomeTools followed the traditional approach to generate a spectral library by synthesizing unique tryptic peptides from the human proteome and acquiring MS/MS data on multiple instrument platforms . This was subsequently expanded to include additional tryptic peptides and modified peptides , non-tryptic peptides , and isobarically labeled peptides to currently consist of more than one million unique synthetic peptides and over 14 million MS/MS spectra. In contrast, MassIVE-KB employed a data-driven approach towards spectral library creation by re-analyzing hundreds of millions to billions of public MS/MS spectra on the MassIVE data repository using sequence database searching (M. . The most confidently identified MS/MS spectra and their peptide labels were then extracted to create the MassIVE-KB human peptide spectral library, which currently contains 2.5 million unique peptides and 6 million MS/MS spectra (version 2.0.15). Although an equivalent strategy to sequence database searching in proteomics currently does not exist for metabolomics, approaches employed by ProteomeTools and MassIVE-KB demonstrate how alternative strategies can be used to create valuable collections of reference MS/MS spectra. Furthermore, as it is not uncommon to observe peptides in metabolomics data, it is conceivable that proteomics libraries can be repurposed to also inform a subset of metabolomics data through creative use of algorithms that find analogs of peptides or peptidic molecules.