Title |
Seq2Ref: a web server to facilitate functional interpretation
|
---|---|
Published in |
BMC Bioinformatics, January 2013
|
DOI | 10.1186/1471-2105-14-30 |
Pubmed ID | |
Authors |
Wenlin Li, Qian Cong, Lisa N Kinch, Nick V Grishin |
Abstract |
The size of the protein sequence database has been exponentially increasing due to advances in genome sequencing. However, experimentally characterized proteins only constitute a small portion of the database, such that the majority of sequences have been annotated by computational approaches. Current automatic annotation pipelines inevitably introduce errors, making the annotations unreliable. Instead of such error-prone automatic annotations, functional interpretation should rely on annotations of 'reference proteins' that have been experimentally characterized or manually curated. |
X Demographics
The data shown below were collected from the profiles of 5 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 States | 2 | 40% |
Luxembourg | 1 | 20% |
China | 1 | 20% |
Unknown | 1 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 2% |
Brazil | 1 | 2% |
India | 1 | 2% |
Czechia | 1 | 2% |
United Kingdom | 1 | 2% |
Unknown | 38 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 15 | 35% |
Professor > Associate Professor | 7 | 16% |
Student > Ph. D. Student | 6 | 14% |
Professor | 4 | 9% |
Student > Bachelor | 3 | 7% |
Other | 7 | 16% |
Unknown | 1 | 2% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 25 | 58% |
Biochemistry, Genetics and Molecular Biology | 7 | 16% |
Computer Science | 3 | 7% |
Medicine and Dentistry | 3 | 7% |
Engineering | 3 | 7% |
Other | 1 | 2% |
Unknown | 1 | 2% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 17 April 2013.
All research outputs
#12,676,336
of 22,694,633 outputs
Outputs from BMC Bioinformatics
#3,619
of 7,254 outputs
Outputs of similar age
#150,528
of 282,151 outputs
Outputs of similar age from BMC Bioinformatics
#70
of 137 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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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 is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.