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Mendeley readers
Attention Score in Context
| Title |
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
|
|---|---|
| Published in |
BMC Bioinformatics, February 2010
|
| DOI | 10.1186/1471-2105-11-79 |
| Pubmed ID | |
| Authors |
Maria Pamela C David, Gisela P Concepcion, Eduardo A Padlan |
| Abstract |
All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Switzerland | 1 | 2% |
| Austria | 1 | 2% |
| Indonesia | 1 | 2% |
| Japan | 1 | 2% |
| Belgium | 1 | 2% |
| Unknown | 41 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 21% |
| Researcher | 10 | 21% |
| Student > Master | 7 | 15% |
| Student > Bachelor | 5 | 10% |
| Professor | 4 | 8% |
| Other | 8 | 17% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 35% |
| Biochemistry, Genetics and Molecular Biology | 6 | 13% |
| Engineering | 4 | 8% |
| Computer Science | 3 | 6% |
| Chemistry | 2 | 4% |
| Other | 9 | 19% |
| Unknown | 7 | 15% |
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 10 August 2010.
All research outputs
#5,692,997
of 22,705,019 outputs
Outputs from BMC Bioinformatics
#2,120
of 7,254 outputs
Outputs of similar age
#37,739
of 165,122 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 65 outputs
Altmetric has tracked 22,705,019 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
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 has gotten more attention than average, scoring higher than 70% of its peers.
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 165,122 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.