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X Demographics
Mendeley readers
Attention Score in Context
| Title |
On the amyloid datasets used for training PAFIG how (not) to extend the experimental dataset of hexapeptides
|
|---|---|
| Published in |
BMC Bioinformatics, December 2013
|
| DOI | 10.1186/1471-2105-14-351 |
| Pubmed ID | |
| Authors |
Malgorzata Kotulska, Olgierd Unold |
| Abstract |
Amyloids are proteins capable of forming aberrant intramolecular contact sites, characteristic of beta zipper configuration. Amyloids can underlie serious health conditions, e.g. Alzheimer's or Parkinson's diseases. It has been proposed that short segments of amino acids can be responsible for protein amyloidogenicity, but no more than two hundred such hexapeptides have been experimentally found. The authors of the computational tool Pafig published in BMC Bioinformatics a method for extending the amyloid hexapeptide dataset that could be used for training and testing models. They assumed that all hexapeptides belonging to an amyloid protein can be regarded as amylopositive, while those from proteins never reported as amyloid are always amylonegative. Here we show why the above described method of extending datasets is wrong and discuss the reasons why the incorrect data could lead to falsely correct classification. |
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 % |
|---|---|---|
| Norway | 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 29% |
| Student > Ph. D. Student | 4 | 17% |
| Professor > Associate Professor | 3 | 13% |
| Student > Bachelor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 5 | 21% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 25% |
| Medicine and Dentistry | 5 | 21% |
| Computer Science | 4 | 17% |
| Agricultural and Biological Sciences | 2 | 8% |
| Engineering | 2 | 8% |
| Other | 4 | 17% |
| Unknown | 1 | 4% |
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 05 December 2013.
All research outputs
#20,211,690
of 22,733,113 outputs
Outputs from BMC Bioinformatics
#6,838
of 7,266 outputs
Outputs of similar age
#267,247
of 306,889 outputs
Outputs of similar age from BMC Bioinformatics
#99
of 107 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 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 1st percentile – i.e., 1% 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 306,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.