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 |
Construction of gene regulatory networks using biclustering and bayesian networks
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, October 2011
|
| DOI | 10.1186/1742-4682-8-39 |
| Pubmed ID | |
| Authors |
Fadhl M Alakwaa, Nahed H Solouma, Yasser M Kadah |
| Abstract |
Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Germany | 1 | 1% |
| Belgium | 1 | 1% |
| Unknown | 70 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 28% |
| Researcher | 16 | 22% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Professor | 4 | 5% |
| Other | 10 | 14% |
| Unknown | 9 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 32% |
| Agricultural and Biological Sciences | 18 | 24% |
| Biochemistry, Genetics and Molecular Biology | 6 | 8% |
| Mathematics | 4 | 5% |
| Engineering | 4 | 5% |
| Other | 9 | 12% |
| Unknown | 9 | 12% |
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 03 November 2011.
All research outputs
#13,356,164
of 22,655,397 outputs
Outputs from Theoretical Biology and Medical Modelling
#137
of 286 outputs
Outputs of similar age
#85,683
of 139,896 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#5
of 8 outputs
Altmetric has tracked 22,655,397 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 286 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 49th percentile – i.e., 49% 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 139,896 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.