Evidence map›Paper›PMID 26122521›Full record

ArticleJournal of the American Society for Mass Spectrometry2015

Novor: real-time peptide de novo sequencing software.

Bin Ma

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.

0numbers the graph read from it
0cells of the map it votes in
107citing 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

107 citing papers in PubMed.

  1. Article
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  8. Discovery of Iron-Chelating Peptides fromFoods (Basel, Switzerland) · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Mass Spectrometry-Based Validation of Chimeric RNAs.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

47 more citing papers are in PubMed but not listed here.

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

1 author.

Bin MaSchool of Computer Science, University of Waterloo, 200 University Ave. W., Waterloo, ON, N2L3G1, Canada. binma@uwaterloo.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

De novo sequencing software has been widely used in proteomics to sequence new peptides from tandem mass spectrometry data. This study presents a new software tool, Novor, to greatly improve both the speed and accuracy of today's peptide de novo sequencing analyses. To improve the accuracy, Novor's scoring functions are based on two large decision trees built from a peptide spectral library with more than 300,000 spectra with machine learning. Important knowledge about peptide fragmentation is extracted automatically from the library and incorporated into the scoring functions. The decision tree model also enables efficient score calculation and contributes to the speed improvement. To further improve the speed, a two-stage algorithmic approach, namely dynamic programming and refinement, is used. The software program was also carefully optimized. On the testing datasets, Novor sequenced 7%-37% more correct residues than the state-of-the-art de novo sequencing tool, PEAKS, while being an order of magnitude faster. Novor can de novo sequence more than 300 MS/MS spectra per second on a laptop computer. The speed surpasses the acquisition speed of today's mass spectrometer and, therefore, opens a new possibility to de novo sequence in real time while the spectrometer is acquiring the spectral data. Graphical Abstract ᅟ.

Indexed as

SoftwareAlgorithmsAnimalsCaenorhabditis elegans ProteinsDatabases, ProteinDecision TreesHumansPeptide FragmentsSequence Analysis, ProteinTandem Mass SpectrometryCaenorhabditis elegans ProteinsPeptide FragmentsDecision treePeptide de novo sequencingReal timeSoftwareTandem mass spectrometry

Identifiers

PMID26122521
PMCPMC4604512

What OpenQuestion holds

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Registered trials

None linked

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.