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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Differential expression of microRNAs as predictors of glioblastoma phenotypes
|
|---|---|
| Published in |
BMC Bioinformatics, January 2014
|
| DOI | 10.1186/1471-2105-15-21 |
| Pubmed ID | |
| Authors |
Barrie S Bradley, Joseph C Loftus, Clinton J Mielke, Valentin Dinu |
| Abstract |
Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion. |
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 % |
|---|---|---|
| Unknown | 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 32 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 24% |
| Student > Master | 7 | 21% |
| Researcher | 7 | 21% |
| Student > Bachelor | 4 | 12% |
| Other | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 3 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 32% |
| Medicine and Dentistry | 9 | 26% |
| Biochemistry, Genetics and Molecular Biology | 3 | 9% |
| Computer Science | 2 | 6% |
| Business, Management and Accounting | 1 | 3% |
| Other | 4 | 12% |
| Unknown | 4 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 20 January 2014.
All research outputs
#14,771,194
of 22,739,983 outputs
Outputs from BMC Bioinformatics
#5,039
of 7,267 outputs
Outputs of similar age
#181,393
of 304,982 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 99 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,267 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 26th percentile – i.e., 26% 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 304,982 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.