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Mendeley readers
Attention Score in Context
| Title |
A survey of DNA motif finding algorithms
|
|---|---|
| Published in |
BMC Bioinformatics, November 2007
|
| DOI | 10.1186/1471-2105-8-s7-s21 |
| Pubmed ID | |
| Authors |
Modan K Das, Ho-Kwok Dai |
| Abstract |
Unraveling the mechanisms that regulate gene expression is a major challenge in biology. An important task in this challenge is to identify regulatory elements, especially the binding sites in deoxyribonucleic acid (DNA) for transcription factors. These binding sites are short DNA segments that are called motifs. Recent advances in genome sequence availability and in high-throughput gene expression analysis technologies have allowed for the development of computational methods for motif finding. As a result, a large number of motif finding algorithms have been implemented and applied to various motif models over the past decade. This survey reviews the latest developments in DNA motif finding algorithms. |
Mendeley readers
The data shown below were compiled from readership statistics for 659 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 19 | 3% |
| United Kingdom | 11 | 2% |
| Spain | 5 | <1% |
| Germany | 4 | <1% |
| France | 4 | <1% |
| China | 3 | <1% |
| Canada | 3 | <1% |
| Australia | 3 | <1% |
| Finland | 3 | <1% |
| Other | 31 | 5% |
| Unknown | 573 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 204 | 31% |
| Researcher | 140 | 21% |
| Student > Master | 98 | 15% |
| Student > Bachelor | 47 | 7% |
| Professor > Associate Professor | 32 | 5% |
| Other | 75 | 11% |
| Unknown | 63 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 311 | 47% |
| Computer Science | 124 | 19% |
| Biochemistry, Genetics and Molecular Biology | 94 | 14% |
| Engineering | 13 | 2% |
| Physics and Astronomy | 7 | 1% |
| Other | 34 | 5% |
| Unknown | 76 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 31 October 2016.
All research outputs
#6,414,259
of 22,789,566 outputs
Outputs from BMC Bioinformatics
#2,472
of 7,280 outputs
Outputs of similar age
#22,859
of 76,772 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 49 outputs
Altmetric has tracked 22,789,566 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,280 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 gotten more attention than average, scoring higher than 65% 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 76,772 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.