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Mendeley readers
Attention Score in Context
| Title |
OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2010
|
| DOI | 10.1186/1471-2105-11-405 |
| Pubmed ID | |
| Authors |
Philip Wenig, Juergen Odermatt |
| Abstract |
Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform. This work describes a native approach to handle chromatographic data files. The approach can be extended in its functionality such as facilities to detect baselines, to detect, integrate and identify peaks and to compare mass spectra, as well as the ability to internationalize the application. Additionally, filters can be applied on the chromatographic data to enhance its quality, for example to remove background and noise. Extended operations like do, undo and redo are supported. OpenChrom is a software application to edit and analyze mass spectrometric chromatographic data. It is extensible in many different ways, depending on the demands of the users or the analytical procedures and algorithms. It offers a customizable graphical user interface. The software is independent of the operating system, due to the fact that the Rich Client Platform is written in Java. OpenChrom is released under the Eclipse Public License 1.0 (EPL). There are no license constraints regarding extensions. They can be published using open source as well as proprietary licenses. OpenChrom is available free of charge at http://www.openchrom.net. |
Mendeley readers
The data shown below were compiled from readership statistics for 236 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 1% |
| Netherlands | 2 | <1% |
| United States | 2 | <1% |
| Malaysia | 1 | <1% |
| Brazil | 1 | <1% |
| Lithuania | 1 | <1% |
| Sweden | 1 | <1% |
| Belgium | 1 | <1% |
| South Africa | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 223 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 22% |
| Researcher | 52 | 22% |
| Student > Master | 36 | 15% |
| Student > Bachelor | 19 | 8% |
| Student > Postgraduate | 10 | 4% |
| Other | 35 | 15% |
| Unknown | 31 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 68 | 29% |
| Chemistry | 57 | 24% |
| Biochemistry, Genetics and Molecular Biology | 20 | 8% |
| Engineering | 13 | 6% |
| Computer Science | 10 | 4% |
| Other | 29 | 12% |
| Unknown | 39 | 17% |
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 20 April 2021.
All research outputs
#7,463,244
of 22,817,213 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,284 outputs
Outputs of similar age
#33,442
of 94,079 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 55 outputs
Altmetric has tracked 22,817,213 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,284 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 gotten more attention than average, scoring higher than 50% 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 94,079 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.