A pipeline for identifying endogenous neuropeptides from spectral archives Online publication date: Tue, 05-Jun-2018
by Mingze Bai; Mingmin He; Qifeng Sun; Huadong Liao; Kunxian Shu; Henning Hermjakob
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 20, No. 1, 2018
Abstract: Shotgun proteomics experiments often provide a big amount of spectra data; however, a big part of them remain unidentified. Many unidentified spectra that are high probably from peptides could be revealed by data mining methods such as clustering. This idea motivates researchers to build 'spectral archives' to identify more peptides from the previously analysed resources. The objective is to build a general way to identify peptides for these high possibility spectra in spectral archives, to help biologists to get more output from the data. We here propose a novel generic pipeline for this approach, based on the PRIDE cluster resources, rather than building a complete archive from scratch. We applied our pipeline to test the identification of endogenous neuropeptides in rat. 33 high probability peptide-induced spectra have been exposed from rat's unidentified spectra in PRIDE cluster's archive.
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