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A New Parameterized Algorithm for Rapid Peptide Sequencing
De novo sequencing is an important computational approach to determining the amino acid sequence of a peptide with tandem mass spectrometry (MS/MS). Most of the existing approaches use a graph model to describe a spectrum and the sequencing is performed by computing the longest antisymmetric path in...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925086/ https://www.ncbi.nlm.nih.gov/pubmed/24551059 http://dx.doi.org/10.1371/journal.pone.0087476 |
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author | Song, Yinglei |
author_facet | Song, Yinglei |
author_sort | Song, Yinglei |
collection | PubMed |
description | De novo sequencing is an important computational approach to determining the amino acid sequence of a peptide with tandem mass spectrometry (MS/MS). Most of the existing approaches use a graph model to describe a spectrum and the sequencing is performed by computing the longest antisymmetric path in the graph. The task is often computationally intensive since a given MS/MS spectrum often contains noisy data, missing mass peaks, or post translational modifications/mutations. This paper develops a new parameterized algorithm that can efficiently compute the longest antisymmetric partial path in an extended spectrum graph that is of bounded path width. Our testing results show that this algorithm can efficiently process experimental spectra and provide sequencing results of high accuracy. |
format | Online Article Text |
id | pubmed-3925086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39250862014-02-18 A New Parameterized Algorithm for Rapid Peptide Sequencing Song, Yinglei PLoS One Research Article De novo sequencing is an important computational approach to determining the amino acid sequence of a peptide with tandem mass spectrometry (MS/MS). Most of the existing approaches use a graph model to describe a spectrum and the sequencing is performed by computing the longest antisymmetric path in the graph. The task is often computationally intensive since a given MS/MS spectrum often contains noisy data, missing mass peaks, or post translational modifications/mutations. This paper develops a new parameterized algorithm that can efficiently compute the longest antisymmetric partial path in an extended spectrum graph that is of bounded path width. Our testing results show that this algorithm can efficiently process experimental spectra and provide sequencing results of high accuracy. Public Library of Science 2014-02-14 /pmc/articles/PMC3925086/ /pubmed/24551059 http://dx.doi.org/10.1371/journal.pone.0087476 Text en © 2014 Yinglei Song http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Song, Yinglei A New Parameterized Algorithm for Rapid Peptide Sequencing |
title | A New Parameterized Algorithm for Rapid Peptide Sequencing |
title_full | A New Parameterized Algorithm for Rapid Peptide Sequencing |
title_fullStr | A New Parameterized Algorithm for Rapid Peptide Sequencing |
title_full_unstemmed | A New Parameterized Algorithm for Rapid Peptide Sequencing |
title_short | A New Parameterized Algorithm for Rapid Peptide Sequencing |
title_sort | new parameterized algorithm for rapid peptide sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925086/ https://www.ncbi.nlm.nih.gov/pubmed/24551059 http://dx.doi.org/10.1371/journal.pone.0087476 |
work_keys_str_mv | AT songyinglei anewparameterizedalgorithmforrapidpeptidesequencing AT songyinglei newparameterizedalgorithmforrapidpeptidesequencing |