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Mendeley readers
Attention Score in Context
| Title |
Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme
|
|---|---|
| Published in |
PLOS ONE, October 2011
|
| DOI | 10.1371/journal.pone.0025451 |
| Pubmed ID | |
| Authors |
Pascal O. Zinn, Bhanu Majadan, Pratheesh Sathyan, Sanjay K. Singh, Sadhan Majumder, Ferenc A. Jolesz, Rivka R. Colen |
| Abstract |
Despite recent discoveries of new molecular targets and pathways, the search for an effective therapy for Glioblastoma Multiforme (GBM) continues. A newly emerged field, radiogenomics, links gene expression profiles with MRI phenotypes. MRI-FLAIR is a noninvasive diagnostic modality and was previously found to correlate with cellular invasion in GBM. Thus, our radiogenomic screen has the potential to reveal novel molecular determinants of invasion. Here, we present the first comprehensive radiogenomic analysis using quantitative MRI volumetrics and large-scale gene- and microRNA expression profiling in GBM. |
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 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 3% |
| Colombia | 1 | <1% |
| Brazil | 1 | <1% |
| Netherlands | 1 | <1% |
| Spain | 1 | <1% |
| Denmark | 1 | <1% |
| Unknown | 239 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 20% |
| Student > Ph. D. Student | 49 | 19% |
| Student > Doctoral Student | 22 | 9% |
| Student > Master | 21 | 8% |
| Other | 17 | 7% |
| Other | 59 | 23% |
| Unknown | 34 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 76 | 30% |
| Computer Science | 36 | 14% |
| Engineering | 22 | 9% |
| Agricultural and Biological Sciences | 21 | 8% |
| Biochemistry, Genetics and Molecular Biology | 14 | 6% |
| Other | 37 | 15% |
| Unknown | 46 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 24 May 2023.
All research outputs
#4,142,467
of 22,653,392 outputs
Outputs from PLOS ONE
#58,493
of 193,422 outputs
Outputs of similar age
#23,331
of 132,933 outputs
Outputs of similar age from PLOS ONE
#563
of 2,614 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 193,422 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has gotten more attention than average, scoring higher than 68% 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 132,933 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 81% of its contemporaries.
We're also able to compare this research output to 2,614 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.