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Mendeley readers
Attention Score in Context
| Title |
Virtual karyotyping with SNP microarrays reduces uncertainty in the diagnosis of renal epithelial tumors
|
|---|---|
| Published in |
Diagnostic Pathology, November 2008
|
| DOI | 10.1186/1746-1596-3-44 |
| Pubmed ID | |
| Authors |
Jill M Hagenkord, Anil V Parwani, Maureen A Lyons-Weiler, Karla Alvarez, Robert Amato, Zoran Gatalica, Jose M Gonzalez-Berjon, Leif Peterson, Rajiv Dhir, Federico A Monzon |
| Abstract |
Renal epithelial tumors are morphologically, biologically, and clinically heterogeneous. Different morphologic subtypes require specific management due to markedly different prognosis and response to therapy. Each common subtype has characteristic chromosomal gains and losses, including some with prognostic value. However, copy number information has not been readily accessible for clinical purposes and thus has not been routinely used in the diagnostic evaluation of these tumors. This information can be useful for classification of tumors with complex or challenging morphology. 'Virtual karyotypes' generated using SNP arrays can readily detect characteristic chromosomal lesions in paraffin embedded renal tumors and can be used to correctly categorize the common subtypes with performance characteristics that are amenable for routine clinical use. |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 5% |
| Czechia | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 32% |
| Other | 2 | 9% |
| Lecturer | 2 | 9% |
| Student > Postgraduate | 2 | 9% |
| Student > Ph. D. Student | 2 | 9% |
| Other | 3 | 14% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 45% |
| Medicine and Dentistry | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Computer Science | 1 | 5% |
| Unknown | 4 | 18% |
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 19 April 2017.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Diagnostic Pathology
#225
of 1,124 outputs
Outputs of similar age
#32,594
of 92,893 outputs
Outputs of similar age from Diagnostic Pathology
#1
of 2 outputs
Altmetric has tracked 22,783,848 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 1,124 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 74% 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 92,893 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them