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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MotifLab: a tools and data integration workbench for motif discovery and regulatory sequence analysis
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-9 |
| Pubmed ID | |
| Authors |
Kjetil Klepper, Finn Drabløs |
| Abstract |
Traditional methods for computational motif discovery often suffer from poor performance. In particular, methods that search for sequence matches to known binding motifs tend to predict many non-functional binding sites because they fail to take into consideration the biological state of the cell. In recent years, genome-wide studies have generated a lot of data that has the potential to improve our ability to identify functional motifs and binding sites, such as information about chromatin accessibility and epigenetic states in different cell types. However, it is not always trivial to make use of this data in combination with existing motif discovery tools, especially for researchers who are not skilled in bioinformatics programming. |
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 % |
|---|---|---|
| United Kingdom | 2 | 50% |
| United States | 1 | 25% |
| Norway | 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| Germany | 4 | 3% |
| Australia | 2 | 2% |
| United Kingdom | 1 | <1% |
| Finland | 1 | <1% |
| Spain | 1 | <1% |
| Mexico | 1 | <1% |
| Unknown | 100 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 37 | 32% |
| Student > Ph. D. Student | 24 | 21% |
| Student > Master | 16 | 14% |
| Professor > Associate Professor | 8 | 7% |
| Student > Bachelor | 7 | 6% |
| Other | 13 | 11% |
| Unknown | 10 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 50 | 43% |
| Biochemistry, Genetics and Molecular Biology | 25 | 22% |
| Computer Science | 16 | 14% |
| Medicine and Dentistry | 4 | 3% |
| Engineering | 2 | 2% |
| Other | 5 | 4% |
| Unknown | 13 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 06 February 2013.
All research outputs
#2,699,539
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#832
of 7,400 outputs
Outputs of similar age
#28,508
of 289,152 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 137 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 88% 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 289,152 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.