Evidence map›Paper›PMID 33036551›Full record

ArticleBMC bioinformatics2020

Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format.

Stefania Alexandra Iakab, Lluc Sementé, María García-Altares, Xavier Correig, Pere Ràfols

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. 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. Article
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  8. New software tools, databases, and resources in metabolomics: updates from 2020.Metabolomics : Official journal of the Metabolomic Society · 2021
    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

5 authors.

Stefania Alexandra IakabDepartment of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.
Lluc SementéDepartment of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.
María García-AltaresDepartment of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain. maria.garcia-altares@urv.cat.ORCID http://orcid.org/0000-0003-4255-1487
Xavier CorreigDepartment of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.
Pere RàfolsDepartment of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca 2017-SGR-1119Agència de Gestió d'Ajuts Universitaris i de Recerca 2018 BP 00188Ministerio de Ciencia, Innovación y Universidades RTI2018-096061-B-I00Ministerio de Economía y Competitividad BES-2016-076483Universitat Rovira i Virgili 2017PMF-PIPF-60
6 · The paper itself

Abstract

backgroundMultimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand.

resultsRaman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications.

conclusionRaman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis.

Indexed as

Mass SpectrometryMolecular ImagingSpectrum Analysis, RamanImage Processing, Computer-AssistedReference StandardsConverterimzMLMass spectrometry imagingRRaman imaging

Identifiers

PMID33036551
PMCPMC7547406

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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.