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X Demographics
Mendeley readers
Attention Score in Context
| Title |
KeyPathwayMiner 4.0: condition-specific pathway analysis by combining multiple omics studies and networks with Cytoscape
|
|---|---|
| Published in |
BMC Systems Biology, August 2014
|
| DOI | 10.1186/s12918-014-0099-x |
| Pubmed ID | |
| Authors |
Nicolas Alcaraz, Josch Pauling, Richa Batra, Eudes Barbosa, Alexander Junge, Anne GL Christensen, Vasco Azevedo, Henrik J Ditzel, Jan Baumbach |
| Abstract |
Over the last decade network enrichment analysis has become popular in computational systems biology to elucidate aberrant network modules. Traditionally, these approaches focus on combining gene expression data with protein-protein interaction (PPI) networks. Nowadays, the so-called omics technologies allow for inclusion of many more data sets, e.g. protein phosphorylation or epigenetic modifications. This creates a need for analysis methods that can combine these various sources of data to obtain a systems-level view on aberrant biological networks. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 2 | 33% |
| Germany | 1 | 17% |
| Japan | 1 | 17% |
| France | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 4 | 3% |
| United States | 2 | 2% |
| Brazil | 1 | <1% |
| France | 1 | <1% |
| Spain | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 115 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 28% |
| Student > Ph. D. Student | 25 | 20% |
| Student > Master | 19 | 15% |
| Student > Bachelor | 12 | 10% |
| Professor > Associate Professor | 8 | 6% |
| Other | 11 | 9% |
| Unknown | 15 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 22% |
| Biochemistry, Genetics and Molecular Biology | 27 | 22% |
| Computer Science | 25 | 20% |
| Medicine and Dentistry | 9 | 7% |
| Immunology and Microbiology | 3 | 2% |
| Other | 11 | 9% |
| Unknown | 23 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 04 December 2014.
All research outputs
#7,388,356
of 22,760,687 outputs
Outputs from BMC Systems Biology
#309
of 1,142 outputs
Outputs of similar age
#74,682
of 235,512 outputs
Outputs of similar age from BMC Systems Biology
#7
of 25 outputs
Altmetric has tracked 22,760,687 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 72% 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 235,512 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 25 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 72% of its contemporaries.