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Mendeley readers
Attention Score in Context
| Title |
SFSSClass: an integrated approach for miRNA based tumor classification
|
|---|---|
| Published in |
BMC Bioinformatics, January 2010
|
| DOI | 10.1186/1471-2105-11-s1-s22 |
| Pubmed ID | |
| Authors |
Ramkrishna Mitra, Sanghamitra Bandyopadhyay, Ujjwal Maulik, Michael Q Zhang |
| Abstract |
MicroRNA (miRNA) expression profiling data has recently been found to be particularly important in cancer research and can be used as a diagnostic and prognostic tool. Current approaches of tumor classification using miRNA expression data do not integrate the experimental knowledge available in the literature. A judicious integration of such knowledge with effective miRNA and sample selection through a biclustering approach could be an important step in improving the accuracy of tumor classification. |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 9% |
| Spain | 1 | 3% |
| Unknown | 31 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 31% |
| Student > Ph. D. Student | 9 | 26% |
| Professor > Associate Professor | 5 | 14% |
| Lecturer | 2 | 6% |
| Student > Bachelor | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 2 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 40% |
| Computer Science | 8 | 23% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Medicine and Dentistry | 2 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 2 | 6% |
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 06 April 2012.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#48,563
of 164,255 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 58 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 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 50% 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 164,255 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.