Evidence map›Paper›PMID 27187201›Full record

ArticleBioinformatics (Oxford, England)2016

Top-down analysis of protein samples by de novo sequencing techniques.

Kira Vyatkina, Si Wu, Lennard J M Dekker, Martijn M VanDuijn, Xiaowen Liu, Nikola Tolić, Theo M Luider, Ljiljana Paša-Tolić, Pavel A Pevzner

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. ResNeXt-Based Rescoring Model for Proteoform Characterization in Top-Down Mass Spectra.Interdisciplinary sciences, computational life sciences · 2025
    Article
  3. Top-Down and Middle-Down Mass Spectrometry of Antibodies.Molecular & cellular proteomics : MCP · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Top-Down Proteomics: Ready for Prime Time?Analytical chemistry · 2018
    Review
  9. Article
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

9 authors.

Kira VyatkinaAlgorithmic Biology Laboratory, Saint Petersburg Academic University, St Petersburg, Russia Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, St Petersburg, Russia.
Si WuDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA.
Lennard J M DekkerDepartment of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Martijn M VanDuijnDepartment of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Xiaowen LiuDepartment of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
Nikola TolićEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Theo M LuiderDepartment of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Ljiljana Paša-TolićEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Pavel A PevznerCenter for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, St Petersburg, Russia Department of Computer Science and Engineering, University of California, San Diego, CA, USA.

Funding

TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
NIGMS NIH HHS P41 GM103484
6 · The paper itself

Abstract

motivationRecent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data.

resultsWe describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequencing of fragments of the proteins present in the sample. Our algorithm takes as input a set of de novo amino acid strings derived from the given mass spectra using the recently proposed Twister approach, and combines them into aggregated strings endowed with offsets. The former typically constitute accurate sequence fragments of sufficiently well-represented proteins from the sample being analyzed, while the latter indicate their location in the protein sequence, and also bear information on post-translational modifications and fragmentation patterns. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://bioinf.spbau.ru/en/twister CONTACT: vyatkina@spbau.ru or ppevzner@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsAmino Acid SequenceProteinsSequence Analysis, ProteinProtein Processing, Post-TranslationalTandem Mass SpectrometryProteins

Identifiers

PMID27187201
PMCPMC6280873

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.