You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
AMBIENT: Active Modules for Bipartite Networks - using high-throughput transcriptomic data to dissect metabolic response
|
|---|---|
| Published in |
BMC Systems Biology, March 2013
|
| DOI | 10.1186/1752-0509-7-26 |
| Pubmed ID | |
| Authors |
William A Bryant, Michael JE Sternberg, John W Pinney |
| Abstract |
With the continued proliferation of high-throughput biological experiments, there is a pressing need for tools to integrate the data produced in ways that produce biologically meaningful conclusions. Many microarray studies have analysed transcriptomic data from a pathway perspective, for instance by testing for KEGG pathway enrichment in sets of upregulated genes. However, the increasing availability of species-specific metabolic models provides the opportunity to analyse these data in a more objective, system-wide manner. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| United States | 1 | 33% |
| Germany | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
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 % |
|---|---|---|
| United Kingdom | 4 | 8% |
| Colombia | 1 | 2% |
| Sweden | 1 | 2% |
| France | 1 | 2% |
| Unknown | 42 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 31% |
| Researcher | 13 | 27% |
| Student > Master | 7 | 14% |
| Other | 5 | 10% |
| Professor > Associate Professor | 3 | 6% |
| Other | 4 | 8% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 41% |
| Computer Science | 14 | 29% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Mathematics | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 4 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 01 September 2013.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from BMC Systems Biology
#556
of 1,132 outputs
Outputs of similar age
#124,131
of 210,199 outputs
Outputs of similar age from BMC Systems Biology
#13
of 22 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 46th percentile – i.e., 46% 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 210,199 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 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.