Literature DB >> 29701026

[Progress in the spectral library based protein identification strategy].

Derui Yu1,2, Jie Ma2, Zengyan Xie1, Mingze Bai1, Yunping Zhu2, Kunxian Shu1.   

Abstract

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

Keywords:  protein identification; spectral libraries; spectral library searching; spectrum clustering; tandem mass spectrometry

Mesh:

Substances:

Year:  2018        PMID: 29701026     DOI: 10.13345/j.cjb.170321

Source DB:  PubMed          Journal:  Sheng Wu Gong Cheng Xue Bao        ISSN: 1000-3061


  1 in total

1.  Deep learning embedder method and tool for mass spectra similarity search.

Authors:  Chunyuan Qin; Xiyang Luo; Chuan Deng; Kunxian Shu; Weimin Zhu; Johannes Griss; Henning Hermjakob; Mingze Bai; Yasset Perez-Riverol
Journal:  J Proteomics       Date:  2020-12-08       Impact factor: 3.855

  1 in total

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