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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Establishing and Maintaining an Extensive Library of Patient-Derived Xenograft Models
|
|---|---|
| Published in |
Frontiers in oncology, February 2018
|
| DOI | 10.3389/fonc.2018.00019 |
| Pubmed ID | |
| Authors |
Marissa Mattar, Craig R. McCarthy, Amanda R. Kulick, Besnik Qeriqi, Sean Guzman, Elisa de Stanchina |
| Abstract |
Patient-derived xenograft (PDX) models have recently emerged as a highly desirable platform in oncology and are expected to substantially broaden the way in vivo studies are designed and executed and to reshape drug discovery programs. However, acquisition of patient-derived samples, and propagation, annotation and distribution of PDXs are complex processes that require a high degree of coordination among clinic, surgery and laboratory personnel, and are fraught with challenges that are administrative, procedural and technical. Here, we examine in detail the major aspects of this complex process and relate our experience in establishing a PDX Core Laboratory within a large academic institution. |
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 % |
|---|---|---|
| Switzerland | 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 18% |
| Student > Bachelor | 7 | 12% |
| Researcher | 7 | 12% |
| Other | 4 | 7% |
| Librarian | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 17 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 15% |
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Engineering | 4 | 7% |
| Social Sciences | 3 | 5% |
| Agricultural and Biological Sciences | 3 | 5% |
| Other | 12 | 20% |
| Unknown | 21 | 35% |
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 06 September 2019.
All research outputs
#5,341,501
of 25,382,440 outputs
Outputs from Frontiers in oncology
#1,862
of 22,428 outputs
Outputs of similar age
#96,237
of 344,213 outputs
Outputs of similar age from Frontiers in oncology
#25
of 103 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,428 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 91% 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 344,213 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 71% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.