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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Network topology-based detection of differential gene regulation and regulatory switches in cell metabolism and signaling
|
|---|---|
| Published in |
BMC Systems Biology, May 2014
|
| DOI | 10.1186/1752-0509-8-56 |
| Pubmed ID | |
| Authors |
Rosario M Piro, Stefan Wiesberg, Gunnar Schramm, Nico Rebel, Marcus Oswald, Roland Eils, Gerhard Reinelt, Rainer König |
| Abstract |
Common approaches to pathway analysis treat pathways merely as lists of genes disregarding their topological structures, that is, ignoring the genes' interactions on which a pathway's cellular function depends. In contrast, PathWave has been developed for the analysis of high-throughput gene expression data that explicitly takes the topology of networks into account to identify both global dysregulation of and localized (switch-like) regulatory shifts within metabolic and signaling pathways. For this purpose, it applies adjusted wavelet transforms on optimized 2D grid representations of curated pathway maps. |
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 % |
|---|---|---|
| Unknown | 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| Germany | 1 | 1% |
| Australia | 1 | 1% |
| Turkey | 1 | 1% |
| China | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 68 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 25% |
| Researcher | 16 | 21% |
| Student > Master | 6 | 8% |
| Professor | 5 | 6% |
| Student > Bachelor | 4 | 5% |
| Other | 15 | 19% |
| Unknown | 12 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 40% |
| Biochemistry, Genetics and Molecular Biology | 12 | 16% |
| Computer Science | 7 | 9% |
| Engineering | 4 | 5% |
| Medicine and Dentistry | 4 | 5% |
| Other | 7 | 9% |
| Unknown | 12 | 16% |
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 03 June 2014.
All research outputs
#19,015,492
of 23,577,654 outputs
Outputs from BMC Systems Biology
#833
of 1,139 outputs
Outputs of similar age
#165,834
of 228,550 outputs
Outputs of similar age from BMC Systems Biology
#21
of 29 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,139 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% 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 228,550 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.