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Mendeley readers
Attention Score in Context
| Title |
Enzyme classification with peptide programs: a comparative study
|
|---|---|
| Published in |
BMC Bioinformatics, July 2009
|
| DOI | 10.1186/1471-2105-10-231 |
| Pubmed ID | |
| Authors |
Daniel Faria, António EN Ferreira, André O Falcão |
| Abstract |
Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length. |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 6% |
| India | 1 | 6% |
| Portugal | 1 | 6% |
| Romania | 1 | 6% |
| Unknown | 14 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 28% |
| Student > Bachelor | 3 | 17% |
| Professor | 2 | 11% |
| Professor > Associate Professor | 2 | 11% |
| Student > Ph. D. Student | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 3 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 28% |
| Computer Science | 5 | 28% |
| Chemical Engineering | 1 | 6% |
| Physics and Astronomy | 1 | 6% |
| Social Sciences | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 4 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 August 2011.
All research outputs
#15,238,442
of 22,656,971 outputs
Outputs from BMC Bioinformatics
#5,353
of 7,236 outputs
Outputs of similar age
#93,475
of 110,277 outputs
Outputs of similar age from BMC Bioinformatics
#26
of 32 outputs
Altmetric has tracked 22,656,971 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
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 is in the 18th percentile – i.e., 18% 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 110,277 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.