↓ Skip to main content

JS-MS: a cross-platform, modular javascript viewer for mass spectrometry signals

Overview of attention for article published in BMC Bioinformatics, November 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
4 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
JS-MS: a cross-platform, modular javascript viewer for mass spectrometry signals
Published in
BMC Bioinformatics, November 2017
DOI 10.1186/s12859-017-1883-6
Pubmed ID
Authors

Jebediah Rosen, Kyle Handy, André Gillan, Rob Smith

Abstract

Despite the ubiquity of mass spectrometry (MS), data processing tools can be surprisingly limited. To date, there is no stand-alone, cross-platform 3-D visualizer for MS data. Available visualization toolkits require large libraries with multiple dependencies and are not well suited for custom MS data processing modules, such as MS storage systems or data processing algorithms. We present JS-MS, a 3-D, modular JavaScript client application for viewing MS data. JS-MS provides several advantages over existing MS viewers, such as a dependency-free, browser-based, one click, cross-platform install and better navigation interfaces. The client includes a modular Java backend with a novel streaming.mzML parser to demonstrate the API-based serving of MS data to the viewer. JS-MS enables custom MS data processing and evaluation by providing fast, 3-D visualization using improved navigation without dependencies. JS-MS is publicly available with a GPLv2 license at github.com/optimusmoose/jsms.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 21%
Student > Ph. D. Student 4 21%
Student > Master 3 16%
Researcher 3 16%
Student > Bachelor 2 11%
Other 1 5%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 32%
Computer Science 4 21%
Biochemistry, Genetics and Molecular Biology 3 16%
Engineering 2 11%
Chemistry 1 5%
Other 0 0%
Unknown 3 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 09 November 2017.
All research outputs
#3,706,136
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#1,299
of 7,418 outputs
Outputs of similar age
#66,979
of 332,184 outputs
Outputs of similar age from BMC Bioinformatics
#19
of 136 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 82% 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 332,184 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.