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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Tissue-based Alzheimer gene expression markers–comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets
|
|---|---|
| Published in |
BMC Bioinformatics, October 2012
|
| DOI | 10.1186/1471-2105-13-266 |
| Pubmed ID | |
| Authors |
Lena Scheubert, Mitja Luštrek, Rainer Schmidt, Dirk Repsilber, Georg Fuellen |
| Abstract |
Alzheimer's disease has been known for more than 100 years and the underlying molecular mechanisms are not yet completely understood. The identification of genes involved in the processes in Alzheimer affected brain is an important step towards such an understanding. Genes differentially expressed in diseased and healthy brains are promising candidates. |
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 % |
|---|---|---|
| Canada | 1 | 20% |
| United Kingdom | 1 | 20% |
| Australia | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| United Kingdom | 1 | 1% |
| France | 1 | 1% |
| Unknown | 65 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 19% |
| Researcher | 12 | 17% |
| Student > Bachelor | 8 | 12% |
| Other | 5 | 7% |
| Professor > Associate Professor | 5 | 7% |
| Other | 16 | 23% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 23% |
| Biochemistry, Genetics and Molecular Biology | 15 | 22% |
| Agricultural and Biological Sciences | 8 | 12% |
| Medicine and Dentistry | 5 | 7% |
| Engineering | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 15 | 22% |
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 05 December 2012.
All research outputs
#6,915,761
of 22,681,577 outputs
Outputs from BMC Bioinformatics
#2,682
of 7,252 outputs
Outputs of similar age
#51,402
of 174,094 outputs
Outputs of similar age from BMC Bioinformatics
#39
of 110 outputs
Altmetric has tracked 22,681,577 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,252 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 61% 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 174,094 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 68% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.