©1996-2019 All Rights Reserved. Online Journal of Bioinformatics . You may not store these pages in any form except for your own personal use. All other usage or distribution is illegal under international copyright treaties. Permission to use any of these pages in any other way besides the  before mentioned must be gained in writing from the publisher. This article is exclusively copyrighted in its entirety to OJB publications. This article may be copied once but may not be, reproduced or  re-transmitted without the express permission of the editors. This journal satisfies the refereeing requirements (DEST) for the Higher Education Research Data Collection (Australia)  Linking: To link to this page or any pages linking to this page you must link directly to this page only here rather than put up your own page.


OJBTM

 

Online Journal of Bioinformatics ©

 

Volume 6 (2) 174-183, 2005.


Boosting Speed of MS/MS Peptide Sequencing via Database Search by Spectral Profile Comparison.

 

Liu J, Carrillo B, Yanofsky C, Beaudrie C, Morales F, Kearney R.

 

Department of Biomedical Engineering, McGill University, Montreal Quebec, Canada.

 

ABSTRACT

Liu J, Carrillo B, Yanofsky C, Beaudrie C, Morales F, Kearney R., Boosting Speed of MS/MS Peptide Sequencing via Database Search by Spectral Profile Comparison. Onl J Bioinform., 2 (6) 174-183, 2005. In proteomics, tandem mass spectrometry is the key technology for peptide sequencing. The analysis of MS/MS spectra is not always straight due to problems such as noise and missing ions. Many sophisticated methods have been proposed to sequence peptides through tandem mass spectra. While the solutions are capable of providing more robust and accurate results, they are also computationally expensive, creating a bottleneck in high throughput peptide identification. In this work, we introduce a novel method to accelerate speed of peptide sequencing. In contrast to existing approaches, we first conduct a coarse comparison of spectral profiles to drastically shrink the number of candidate peptides. A fast algorithm has been developed to achieve this goal. We show that this approach can significantly improve the speed of peptide sequencing with little damage on the accuracy. Since this approach can be used as an independent preprocessing step, it can be readily coupled with other database search programs for MS/MS analysis

Keywords: proteomics, tandem mass spectrometry, peptide sequencing, database search.


 MAIN

 

FULL-TEXT (SUBSCRIBE OR PURCHASE TITLE)