Evidence map›Paper›PMID 23306530›Full record

ArticleMolecular & cellular proteomics : MCP2013

An adaptive alignment algorithm for quality-controlled label-free LC-MS.

Marianne Sandin, Ashfaq Ali, Karin Hansson, Olle Månsson, Erik Andreasson, Svante Resjö, Fredrik Levander

Abstract readComparative Study
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Proteomics of PTI and Two ETI Immune Reactions in Potato Leaves.International journal of molecular sciences · 2019
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Proteomic Analysis ofMolecular & cellular proteomics : MCP · 2017
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014
    Review
  17. Article
  18. Article
  19. Article
  20. 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

7 authors.

Marianne SandinDepartment of Immunotechnology, Lund University, BMC D13, 22184 Lund, Sweden.
Ashfaq Ali
Karin Hansson
Olle Månsson
Erik Andreasson
Svante Resjö
Fredrik Levander

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Label-free quantification using precursor-based intensities is a versatile workflow for large-scale proteomics studies. The method however requires extensive computational analysis and is therefore in need of robust quality control during the data mining stage. We present a new label-free data analysis workflow integrated into a multiuser software platform. A novel adaptive alignment algorithm has been developed to minimize the possible systematic bias introduced into the analysis. Parameters are estimated on the fly from the data at hand, producing a user-friendly analysis suite. Quality metrics are output in every step of the analysis as well as actively incorporated into the parameter estimation. We furthermore show the improvement of this system by comprehensive comparison to classical label-free analysis methodology as well as current state-of-the-art software.

Indexed as

SoftwareAlgorithmsChromatography, LiquidPhytophthora infestansPlant DiseasesPlant ProteinsProteomeProteomicsQuality ControlSolanum tuberosumTandem Mass SpectrometryPlant ProteinsProteome

Identifiers

PMID23306530
PMCPMC3650348

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.