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

Результат исследований: Научные публикации в периодических изданияхстатья

Выдержка

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%.

Язык оригиналаанглийский
Номер статьиbtz374
Страницы (с-по)i315–i323
Число страниц9
ЖурналBioinformatics
Том35
Номер выпуска14
DOI
СостояниеОпубликовано - 15 июл 2019

Отпечаток

Statistical Significance
Computational methods
Biological Products
Scoring
Medicine
Mass spectrometry
Pipelines
Throughput
Statistical Learning
Mass Spectrometry
Computational Methods
High Throughput
Learning
Databases
Technology
Demonstrate

Предметные области Scopus

  • Теория вероятности и статистика
  • Биохимия
  • Молекулярная биология
  • Прикладные компьютерные науки
  • Математика и теория расчета
  • Вычислительная математика

Цитировать

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abstract = "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{\%}.",
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NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches. / Tagirdzhanov, A.M.; Shlemov, A.; Gurevich, A.

В: Bioinformatics, Том 35, № 14, btz374, 15.07.2019, стр. i315–i323.

Результат исследований: Научные публикации в периодических изданияхстатья

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