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LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data

The spatial distribution of chemical elements in different types of samples is an important field in several research areas such as biology, paleontology or biomedicine, among others. Elemental distribution imaging by laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS) is an effe...

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Autores principales: López-Fernández, Hugo, de S. Pessôa, Gustavo, Arruda, Marco A. Z., Capelo-Martínez, José L., Fdez-Riverola, Florentino, Glez-Peña, Daniel, Reboiro-Jato, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116144/
https://www.ncbi.nlm.nih.gov/pubmed/27917244
http://dx.doi.org/10.1186/s13321-016-0178-7
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author López-Fernández, Hugo
de S. Pessôa, Gustavo
Arruda, Marco A. Z.
Capelo-Martínez, José L.
Fdez-Riverola, Florentino
Glez-Peña, Daniel
Reboiro-Jato, Miguel
author_facet López-Fernández, Hugo
de S. Pessôa, Gustavo
Arruda, Marco A. Z.
Capelo-Martínez, José L.
Fdez-Riverola, Florentino
Glez-Peña, Daniel
Reboiro-Jato, Miguel
author_sort López-Fernández, Hugo
collection PubMed
description The spatial distribution of chemical elements in different types of samples is an important field in several research areas such as biology, paleontology or biomedicine, among others. Elemental distribution imaging by laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS) is an effective technique for qualitative and quantitative imaging due to its high spatial resolution and sensitivity. By applying this technique, vast amounts of raw data are generated to obtain high-quality images, essentially making the use of specific LA–ICP–MS imaging software that can process such data absolutely mandatory. Since existing solutions are usually commercial or hard-to-use for average users, this work introduces LA-iMageS, an open-source, free-to-use multiplatform application for fast and automatic generation of high-quality elemental distribution bioimages from LA–ICP–MS data in the PerkinElmer Elan XL format, whose results can be directly exported to external applications for further analysis. A key strength of LA-iMageS is its substantial added value for users, with particular regard to the customization of the elemental distribution bioimages, which allows, among other features, the ability to change color maps, increase image resolution or toggle between 2D and 3D visualizations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0178-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-51161442016-12-02 LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data López-Fernández, Hugo de S. Pessôa, Gustavo Arruda, Marco A. Z. Capelo-Martínez, José L. Fdez-Riverola, Florentino Glez-Peña, Daniel Reboiro-Jato, Miguel J Cheminform Software The spatial distribution of chemical elements in different types of samples is an important field in several research areas such as biology, paleontology or biomedicine, among others. Elemental distribution imaging by laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS) is an effective technique for qualitative and quantitative imaging due to its high spatial resolution and sensitivity. By applying this technique, vast amounts of raw data are generated to obtain high-quality images, essentially making the use of specific LA–ICP–MS imaging software that can process such data absolutely mandatory. Since existing solutions are usually commercial or hard-to-use for average users, this work introduces LA-iMageS, an open-source, free-to-use multiplatform application for fast and automatic generation of high-quality elemental distribution bioimages from LA–ICP–MS data in the PerkinElmer Elan XL format, whose results can be directly exported to external applications for further analysis. A key strength of LA-iMageS is its substantial added value for users, with particular regard to the customization of the elemental distribution bioimages, which allows, among other features, the ability to change color maps, increase image resolution or toggle between 2D and 3D visualizations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-016-0178-7) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-11-18 /pmc/articles/PMC5116144/ /pubmed/27917244 http://dx.doi.org/10.1186/s13321-016-0178-7 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
López-Fernández, Hugo
de S. Pessôa, Gustavo
Arruda, Marco A. Z.
Capelo-Martínez, José L.
Fdez-Riverola, Florentino
Glez-Peña, Daniel
Reboiro-Jato, Miguel
LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title_full LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title_fullStr LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title_full_unstemmed LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title_short LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
title_sort la-images: a software for elemental distribution bioimaging using la–icp–ms data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116144/
https://www.ncbi.nlm.nih.gov/pubmed/27917244
http://dx.doi.org/10.1186/s13321-016-0178-7
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