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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Condition-specific target prediction from motifs and expression
|
|---|---|
| Published in |
Bioinformatics, February 2014
|
| DOI | 10.1093/bioinformatics/btu066 |
| Pubmed ID | |
| Authors |
Guofeng Meng, Martin Vingron |
| Abstract |
It is commonplace to predict targets of transcription factors (TFs) by sequence matching with their binding motifs. However, this ignores the particular condition of the cells. Gene expression data can provide condition-specific information, as is, e.g. exploited in Motif Enrichment Analysis. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 50% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Norway | 1 | 3% |
| Unknown | 27 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 38% |
| Student > Ph. D. Student | 6 | 21% |
| Professor | 3 | 10% |
| Student > Postgraduate | 2 | 7% |
| Student > Master | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 34% |
| Biochemistry, Genetics and Molecular Biology | 7 | 24% |
| Computer Science | 4 | 14% |
| Nursing and Health Professions | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 5 | 17% |
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 October 2014.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from Bioinformatics
#9,770
of 12,809 outputs
Outputs of similar age
#190,763
of 330,518 outputs
Outputs of similar age from Bioinformatics
#144
of 191 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 12,809 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 20th percentile – i.e., 20% 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 330,518 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 191 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.