| Title |
An Open Data Format for Visualization and Analysis of Cross-Linked Mass Spectrometry Results
|
|---|---|
| Published in |
Journal of the American Society for Mass Spectrometry, July 2016
|
| DOI | 10.1007/s13361-016-1435-8 |
| Pubmed ID | |
| Authors |
Michael R. Hoopmann, Luis Mendoza, Eric W. Deutsch, David Shteynberg, Robert L. Moritz |
| Abstract |
Protein-protein interactions are an important element in the understanding of protein function, and chemical cross-linking shotgun mass spectrometry is rapidly becoming a routine approach to identify these specific interfaces and topographical interactions. Protein cross-link data analysis is aided by dozens of algorithm choices, but hindered by a lack of a common format for representing results. Consequently, interoperability between algorithms and pipelines utilizing chemical cross-linking remains a challenge. pepXML is an open, widely-used format for representing spectral search algorithm results that has facilitated information exchange and pipeline development for typical shotgun mass spectrometry analyses. We describe an extension of this format to incorporate cross-linking spectral search results. We demonstrate application of the extension by representing results of multiple cross-linking search algorithms. In addition, we demonstrate adapting existing pepXML-supporting software pipelines to analyze protein cross-linking results formatted in pepXML. Graphical Abstract ᅟ. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 40% |
| Australia | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 4% |
| Unknown | 27 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 39% |
| Student > Master | 7 | 25% |
| Researcher | 3 | 11% |
| Professor > Associate Professor | 2 | 7% |
| Other | 2 | 7% |
| Other | 1 | 4% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 21% |
| Computer Science | 5 | 18% |
| Agricultural and Biological Sciences | 4 | 14% |
| Chemistry | 3 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 4 | 14% |
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 01 August 2016.
All research outputs
#14,256,180
of 25,374,647 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#2,087
of 3,834 outputs
Outputs of similar age
#199,557
of 380,144 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#14
of 39 outputs
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So far Altmetric has tracked 3,834 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.