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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis
|
|---|---|
| Published in |
BMC Bioinformatics, January 2009
|
| DOI | 10.1186/1471-2105-10-4 |
| Pubmed ID | |
| Authors |
Chao Yang, Zengyou He, Weichuan Yu |
| Abstract |
In mass spectrometry (MS) based proteomic data analysis, peak detection is an essential step for subsequent analysis. Recently, there has been significant progress in the development of various peak detection algorithms. However, neither a comprehensive survey nor an experimental comparison of these algorithms is yet available. The main objective of this paper is to provide such a survey and to compare the performance of single spectrum based peak detection methods. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 501 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 1% |
| Germany | 6 | 1% |
| United Kingdom | 5 | <1% |
| Switzerland | 3 | <1% |
| Austria | 3 | <1% |
| Brazil | 3 | <1% |
| South Africa | 3 | <1% |
| France | 2 | <1% |
| Canada | 2 | <1% |
| Other | 10 | 2% |
| Unknown | 457 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 144 | 29% |
| Researcher | 126 | 25% |
| Student > Master | 67 | 13% |
| Student > Bachelor | 28 | 6% |
| Student > Doctoral Student | 24 | 5% |
| Other | 58 | 12% |
| Unknown | 54 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 75 | 15% |
| Computer Science | 70 | 14% |
| Engineering | 68 | 14% |
| Chemistry | 59 | 12% |
| Physics and Astronomy | 51 | 10% |
| Other | 114 | 23% |
| Unknown | 64 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 18 April 2023.
All research outputs
#1,978,387
of 23,578,918 outputs
Outputs from BMC Bioinformatics
#477
of 7,398 outputs
Outputs of similar age
#8,661
of 172,881 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 67 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,398 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 93% 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 172,881 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% 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 has done particularly well, scoring higher than 95% of its contemporaries.