↓ Skip to main content

MSiReader v1.0: Evolving Open-Source Mass Spectrometry Imaging Software for Targeted and Untargeted Analyses

Overview of attention for article published in Journal of the American Society for Mass Spectrometry, September 2017
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

twitter
6 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
203 Dimensions

Readers on

mendeley
125 Mendeley
Title
MSiReader v1.0: Evolving Open-Source Mass Spectrometry Imaging Software for Targeted and Untargeted Analyses
Published in
Journal of the American Society for Mass Spectrometry, September 2017
DOI 10.1007/s13361-017-1809-6
Pubmed ID
Authors

Mark T. Bokhart, Milad Nazari, Kenneth P. Garrard, David C. Muddiman

Abstract

A major update to the mass spectrometry imaging (MSI) software MSiReader is presented, offering a multitude of newly added features critical to MSI analyses. MSiReader is a free, open-source, and vendor-neutral software written in the MATLAB platform and is capable of analyzing most common MSI data formats. A standalone version of the software, which does not require a MATLAB license, is also distributed. The newly incorporated data analysis features expand the utility of MSiReader beyond simple visualization of molecular distributions. The MSiQuantification tool allows researchers to calculate absolute concentrations from quantification MSI experiments exclusively through MSiReader software, significantly reducing data analysis time. An image overlay feature allows the incorporation of complementary imaging modalities to be displayed with the MSI data. A polarity filter has also been incorporated into the data loading step, allowing the facile analysis of polarity switching experiments without the need for data parsing prior to loading the data file into MSiReader. A quality assurance feature to generate a mass measurement accuracy (MMA) heatmap for an analyte of interest has also been added to allow for the investigation of MMA across the imaging experiment. Most importantly, as new features have been added performance has not degraded, in fact it has been dramatically improved. These new tools and the improvements to the performance in MSiReader v1.0 enable the MSI community to evaluate their data in greater depth and in less time. Graphical Abstract ᅟ.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 125 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 30%
Researcher 22 18%
Student > Master 13 10%
Student > Bachelor 9 7%
Student > Doctoral Student 5 4%
Other 10 8%
Unknown 29 23%
Readers by discipline Count As %
Chemistry 48 38%
Biochemistry, Genetics and Molecular Biology 15 12%
Medicine and Dentistry 7 6%
Agricultural and Biological Sciences 6 5%
Computer Science 6 5%
Other 10 8%
Unknown 33 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 February 2023.
All research outputs
#6,429,457
of 25,556,408 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#844
of 3,857 outputs
Outputs of similar age
#91,954
of 325,768 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#5
of 70 outputs
Altmetric has tracked 25,556,408 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,857 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 78% of its peers.
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 325,768 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 71% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.