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NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches

MOTIVATION: Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP ide...

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Detalles Bibliográficos
Autores principales: Tagirdzhanov, Azat M, Shlemov, Alexander, Gurevich, Alexey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612854/
https://www.ncbi.nlm.nih.gov/pubmed/31510666
http://dx.doi.org/10.1093/bioinformatics/btz374
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author Tagirdzhanov, Azat M
Shlemov, Alexander
Gurevich, Alexey
author_facet Tagirdzhanov, Azat M
Shlemov, Alexander
Gurevich, Alexey
author_sort Tagirdzhanov, Azat M
collection PubMed
description MOTIVATION: Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP identification via database search of mass spectra are still in their infancy and could be substantially improved. RESULTS: Here we present NPS, a statistical learning-based approach for scoring PNP–spectrum matches. We incorporated NPS into two leading PNP discovery tools and benchmarked them on millions of natural product mass spectra. The results demonstrate more than 45% increase in the number of identified spectra and 20% more found PNPs at a false discovery rate of 1%. AVAILABILITY AND IMPLEMENTATION: NPS is available as a command line tool and as a web application at http://cab.spbu.ru/software/NPS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-66128542019-07-12 NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches Tagirdzhanov, Azat M Shlemov, Alexander Gurevich, Alexey Bioinformatics Ismb/Eccb 2019 Conference Proceedings MOTIVATION: Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP identification via database search of mass spectra are still in their infancy and could be substantially improved. RESULTS: Here we present NPS, a statistical learning-based approach for scoring PNP–spectrum matches. We incorporated NPS into two leading PNP discovery tools and benchmarked them on millions of natural product mass spectra. The results demonstrate more than 45% increase in the number of identified spectra and 20% more found PNPs at a false discovery rate of 1%. AVAILABILITY AND IMPLEMENTATION: NPS is available as a command line tool and as a web application at http://cab.spbu.ru/software/NPS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-07 2019-07-05 /pmc/articles/PMC6612854/ /pubmed/31510666 http://dx.doi.org/10.1093/bioinformatics/btz374 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Ismb/Eccb 2019 Conference Proceedings
Tagirdzhanov, Azat M
Shlemov, Alexander
Gurevich, Alexey
NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title_full NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title_fullStr NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title_full_unstemmed NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title_short NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
title_sort nps: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches
topic Ismb/Eccb 2019 Conference Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612854/
https://www.ncbi.nlm.nih.gov/pubmed/31510666
http://dx.doi.org/10.1093/bioinformatics/btz374
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