An Approach for Peptide Identification by De Novo Sequencing of Mixture Spectra

peer-reviewed · IEEE/ACM Transactions on Computational Biology and Bioinformatics · 2017

peer-reviewed · IEEE/ACM Transactions on Computational Biology and Bioinformatics · 2017. Yi Liu et al. Mixture spectra occur quite frequently in a typical wet-lab mass spectrometry experiment, which result from…
Date 2017-03-01
Type peer-reviewed
Venue IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Contribution algorithm
DOI 10.1109/tcbb.2015.2407401
Citations (OpenAlex) 7
Venue 2-year citedness 2.33

Abstract

Mixture spectra occur quite frequently in a typical wet-lab mass spectrometry experiment, which result from the concurrent fragmentation of multiple precursors. The ability to efficiently and confidently identify mixture spectra is essential to alleviate the existent bottleneck of low mass spectra identification rate. However, most of the traditional computational methods are not suitable for interpreting mixture spectra, because they still take the assumption that the acquired spectra come from the fragmentation of a single precursor. In this manuscript, we formulate the mixture spectra de novo sequencing problem mathematically, and propose a dynamic programming algorithm for the problem. Additionally, we use both simulated and real mixture spectra data sets to verify the merits of the proposed algorithm.

Authors

  1. Yi Liu · University of Western Ontario, Western University
  2. Bin Ma · Rapid Novor Inc., University of Waterloo, University of Western Ontario, Western University
  3. Kaizhong Zhang · University of Western Ontario, Western University
  4. Gilles Lajoie · University of Western Ontario, Western University

Methods and tools

  • De novo sequencing of mixture spectra (Liu thesis): PhD work on identifying peptides from MIXTURE tandem mass spectra, where two or more peptides co-fragment: formulates the de novo problem for a mixture spectrum and solves it by dynamic programming.

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