| Title |
microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling
|
|---|---|
| Published in |
Journal of the American Society for Mass Spectrometry, June 2017
|
| DOI | 10.1007/s13361-017-1704-1 |
| Pubmed ID | |
| Authors |
Troy J. Comi, Elizabeth K. Neumann, Thanh D. Do, Jonathan V. Sweedler |
| Abstract |
Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 21% |
| India | 1 | 7% |
| France | 1 | 7% |
| Israel | 1 | 7% |
| Netherlands | 1 | 7% |
| Chile | 1 | 7% |
| Kenya | 1 | 7% |
| Unknown | 5 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 57% |
| Scientists | 5 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 48 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 29% |
| Researcher | 9 | 18% |
| Student > Doctoral Student | 5 | 10% |
| Other | 3 | 6% |
| Professor | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 12 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 14 | 29% |
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Engineering | 5 | 10% |
| Computer Science | 4 | 8% |
| Agricultural and Biological Sciences | 3 | 6% |
| Other | 3 | 6% |
| Unknown | 13 | 27% |
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 03 June 2018.
All research outputs
#4,302,355
of 25,382,440 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#383
of 3,835 outputs
Outputs of similar age
#71,554
of 331,588 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#6
of 70 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,835 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 90% 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 331,588 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 78% 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 91% of its contemporaries.