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

Overview of attention for article published in Journal of Cheminformatics, November 2016
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Citations

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18 Dimensions

Readers on

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51 Mendeley
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Title
LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data
Published in
Journal of Cheminformatics, November 2016
DOI 10.1186/s13321-016-0178-7
Pubmed ID
Authors

Hugo López-Fernández, Gustavo de S. Pessôa, Marco A. Z. Arruda, José L. Capelo-Martínez, Florentino Fdez-Riverola, Daniel Glez-Peña, Miguel Reboiro-Jato

Abstract

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.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Other 6 12%
Student > Master 5 10%
Student > Bachelor 5 10%
Student > Doctoral Student 5 10%
Other 16 31%
Unknown 5 10%
Readers by discipline Count As %
Chemistry 18 35%
Earth and Planetary Sciences 5 10%
Environmental Science 3 6%
Computer Science 3 6%
Agricultural and Biological Sciences 2 4%
Other 8 16%
Unknown 12 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 November 2016.
All research outputs
#6,853,333
of 13,481,364 outputs
Outputs from Journal of Cheminformatics
#353
of 544 outputs
Outputs of similar age
#138,456
of 376,918 outputs
Outputs of similar age from Journal of Cheminformatics
#38
of 67 outputs
Altmetric has tracked 13,481,364 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 544 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 376,918 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.