| Title |
Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling
|
|---|---|
| Published in |
BMC Bioinformatics, July 2013
|
| DOI | 10.1186/1471-2105-14-218 |
| Pubmed ID | |
| Authors |
Zeeshan Ahmed, Saman Zeeshan, Claudia Huber, Michael Hensel, Dietmar Schomburg, Richard Münch, Wolfgang Eisenreich, Thomas Dandekar |
| Abstract |
The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and dynamics through the metabolic networks. An open-source software is required that easily and rapidly calculates from mass spectra of labelled metabolites, derivatives and their fragments global isotope excess and isotopomer distribution. |
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 % |
|---|---|---|
| Germany | 1 | 2% |
| Brazil | 1 | 2% |
| United Kingdom | 1 | 2% |
| Belgium | 1 | 2% |
| Russia | 1 | 2% |
| Japan | 1 | 2% |
| Unknown | 43 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 20% |
| Student > Ph. D. Student | 9 | 18% |
| Professor | 5 | 10% |
| Student > Master | 5 | 10% |
| Professor > Associate Professor | 4 | 8% |
| Other | 9 | 18% |
| Unknown | 7 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 41% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Computer Science | 4 | 8% |
| Chemistry | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 10 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 07 July 2014.
All research outputs
#13,903,378
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#4,306
of 7,400 outputs
Outputs of similar age
#104,296
of 195,889 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 97 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 195,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.