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Quantifying similarity between motifs

Overview of attention for article published in Genome Biology, February 2007
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

patent
4 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
1579 Dimensions

Readers on

mendeley
1058 Mendeley
citeulike
22 CiteULike
connotea
3 Connotea
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Title
Quantifying similarity between motifs
Published in
Genome Biology, February 2007
DOI 10.1186/gb-2007-8-2-r24
Pubmed ID
Authors

Shobhit Gupta, John A Stamatoyannopoulos, Timothy L Bailey, William Stafford Noble

Abstract

A common question within the context of de novo motif discovery is whether a newly discovered, putative motif resembles any previously discovered motif in an existing database. To answer this question, we define a statistical measure of motif-motif similarity, and we describe an algorithm, called Tomtom, for searching a database of motifs with a given query motif. Experimental simulations demonstrate the accuracy of Tomtom's E values and its effectiveness in finding similar motifs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,058 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 18 2%
Germany 5 <1%
Italy 4 <1%
France 3 <1%
China 3 <1%
Australia 2 <1%
Netherlands 2 <1%
Japan 2 <1%
United Kingdom 2 <1%
Other 15 1%
Unknown 1002 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 309 29%
Researcher 174 16%
Student > Master 141 13%
Student > Bachelor 95 9%
Student > Doctoral Student 49 5%
Other 142 13%
Unknown 148 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 425 40%
Biochemistry, Genetics and Molecular Biology 283 27%
Computer Science 67 6%
Medicine and Dentistry 23 2%
Engineering 18 2%
Other 76 7%
Unknown 166 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 January 2024.
All research outputs
#5,446,210
of 25,371,288 outputs
Outputs from Genome Biology
#2,945
of 4,467 outputs
Outputs of similar age
#17,592
of 90,633 outputs
Outputs of similar age from Genome Biology
#10
of 26 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 32nd percentile – i.e., 32% 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 90,633 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 70% of its contemporaries.
We're also able to compare this research output to 26 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 61% of its contemporaries.