| Literature DB >> 29503761 |
Runmin Yang1,2, Daming Zhu1, Qiang Kou2, Poomima Bhat-Nakshatri3, Harikrishna Nakshatri3, Si Wu4, Xiaowen Liu2,5.
Abstract
Database search is the main approach for identifying proteoforms using top-down tandem mass spectra. However, it is extremely slow to align a query spectrum against all protein sequences in a large database when the target proteoform that produced the spectrum contains post-translational modifications and/or mutations. As a result, efficient and sensitive protein sequence filtering algorithms are essential for speeding up database search. In this paper, we propose a novel filtering algorithm, which generates spectrum graphs from subspectra of the query spectrum and searches them against the protein database to find good candidates. Compared with the sequence tag and gaped tag approaches, the proposed method circumvents the step of tag extraction, thus simplifying data processing. Experimental results on real data showed that the proposed method achieved both high speed and high sensitivity in protein sequence filtration.Entities:
Keywords: Mass spectrometry; filtering algorithm; spectrum graph
Year: 2017 PMID: 29503761 PMCID: PMC5831147 DOI: 10.1109/BIBM.2017.8217653
Source DB: PubMed Journal: Proceedings (IEEE Int Conf Bioinformatics Biomed) ISSN: 2156-1125