| Title |
MapMi: automated mapping of microRNA loci
|
|---|---|
| Published in |
BMC Bioinformatics, March 2010
|
| DOI | 10.1186/1471-2105-11-133 |
| Pubmed ID | |
| Authors |
José Afonso Guerra-Assunção, Anton J Enright |
| Abstract |
A large effort to discover microRNAs (miRNAs) has been under way. Currently miRBase is their primary repository, providing annotations of primary sequences, precursors and probable genomic loci. In many cases miRNAs are identical or very similar between related (or in some cases more distant) species. However, miRBase focuses on those species for which miRNAs have been directly confirmed. Secondly, specific miRNAs or their loci are sometimes not annotated even in well-covered species. We sought to address this problem by developing a computational system for automated mapping of miRNAs within and across species. Given the sequence of a known miRNA in one species it is relatively straightforward to determine likely loci of that miRNA in other species. Our primary goal is not the discovery of novel miRNAs but the mapping of validated miRNAs in one species to their most likely orthologues in other species. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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 Kingdom | 4 | 3% |
| Germany | 3 | 3% |
| Brazil | 3 | 3% |
| Portugal | 1 | <1% |
| Saudi Arabia | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 102 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 28% |
| Student > Ph. D. Student | 27 | 23% |
| Professor > Associate Professor | 17 | 15% |
| Student > Master | 8 | 7% |
| Student > Postgraduate | 7 | 6% |
| Other | 20 | 17% |
| Unknown | 4 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 64 | 56% |
| Biochemistry, Genetics and Molecular Biology | 24 | 21% |
| Computer Science | 10 | 9% |
| Medicine and Dentistry | 4 | 3% |
| Business, Management and Accounting | 2 | 2% |
| Other | 6 | 5% |
| Unknown | 5 | 4% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 December 2019.
All research outputs
#3,019,607
of 22,656,971 outputs
Outputs from BMC Bioinformatics
#1,066
of 7,236 outputs
Outputs of similar age
#12,236
of 94,084 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 62 outputs
Altmetric has tracked 22,656,971 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,236 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 85% of its peers.
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We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.