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Attention Score in Context
Title |
Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments
|
---|---|
Published in |
Genome Biology, January 2008
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DOI | 10.1186/gb-2008-9-1-r7 |
Pubmed ID | |
Authors |
Brian J Haas, Steven L Salzberg, Wei Zhu, Mihaela Pertea, Jonathan E Allen, Joshua Orvis, Owen White, C Robin Buell, Jennifer R Wortman |
Abstract |
EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation. |
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 % |
---|---|---|
Australia | 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 824 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 1% |
Germany | 3 | <1% |
Brazil | 3 | <1% |
Argentina | 3 | <1% |
Sweden | 3 | <1% |
United Kingdom | 3 | <1% |
Italy | 2 | <1% |
Australia | 2 | <1% |
Netherlands | 2 | <1% |
Other | 14 | 2% |
Unknown | 778 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 163 | 20% |
Researcher | 159 | 19% |
Student > Master | 95 | 12% |
Student > Bachelor | 53 | 6% |
Student > Doctoral Student | 45 | 5% |
Other | 133 | 16% |
Unknown | 176 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 369 | 45% |
Biochemistry, Genetics and Molecular Biology | 163 | 20% |
Computer Science | 17 | 2% |
Unspecified | 14 | 2% |
Environmental Science | 13 | 2% |
Other | 42 | 5% |
Unknown | 206 | 25% |
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 10 February 2021.
All research outputs
#7,960,052
of 25,374,647 outputs
Outputs from Genome Biology
#3,393
of 4,467 outputs
Outputs of similar age
#42,050
of 168,512 outputs
Outputs of similar age from Genome Biology
#18
of 35 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
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 23rd percentile – i.e., 23% 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 168,512 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 74% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.