Evidence map›Paper›PMID 38951578›Full record

ArticleScientific reports2024

PowerNovo: de novo peptide sequencing via tandem mass spectrometry using an ensemble of transformer and BERT models.

Denis V Petrovskiy, Kirill S Nikolsky, Liudmila I Kulikova, Vladimir R Rudnev, Tatiana V Butkova, Kristina A Malsagova, Arthur T Kopylov, Anna L Kaysheva

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Denis V PetrovskiyInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Kirill S NikolskyInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Liudmila I KulikovaInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Vladimir R RudnevInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Tatiana V ButkovaInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Kristina A MalsagovaInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Arthur T KopylovInstitute of Biomedical Chemistry, 119121, Moscow, Russia.
Anna L KayshevaInstitute of Biomedical Chemistry, 119121, Moscow, Russia. kaysheva1@gmail.com.

Funding

Russian Federation Fundamental Research Program for the long-term period for 2021-2030 122092200056-9
6 · The paper itself

Abstract

The primary objective of analyzing the data obtained in a mass spectrometry-based proteomic experiment is peptide and protein identification, or correct assignment of the tandem mass spectrum to one amino acid sequence. Comparison of empirical fragment spectra with the theoretical predicted one or matching with the collected spectra library are commonly accepted strategies of proteins identification and defining of their amino acid sequences. Although these approaches are widely used and are appreciably efficient for the well-characterized model organisms or measured proteins, they cannot detect novel peptide sequences that have not been previously annotated or are rare. This study presents PowerNovo tool for de novo sequencing of proteins using tandem mass spectra acquired in a variety of types of mass analyzers and different fragmentation techniques. PowerNovo involves an ensemble of models for peptide sequencing: model for detecting regularities in tandem mass spectra, precursors, and fragment ions and a natural language processing model, which has a function of peptide sequence quality assessment and helps with reconstruction of noisy sequences. The results of testing showed that the performance of PowerNovo is comparable and even better than widely utilized PointNovo, DeepNovo, Casanovo, and Novor packages. Also, PowerNovo provides complete cycle of processing (pipeline) of mass spectrometry data and, along with predicting the peptide sequence, involves the peptide assembly and protein inference blocks.

Indexed as

PeptidesSequence Analysis, ProteinTandem Mass SpectrometryAlgorithmsAmino Acid SequenceProteomicsSoftwarePeptides

Identifiers

PMID38951578
PMCPMC11217302

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.