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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A novel flow cytometry-based cell capture platform for the detection, capture and molecular characterization of rare tumor cells in blood
|
|---|---|
| Published in |
Journal of Translational Medicine, May 2014
|
| DOI | 10.1186/1479-5876-12-143 |
| Pubmed ID | |
| Authors |
Masaru Watanabe, Masakuni Serizawa, Takeshi Sawada, Kazuo Takeda, Toshiaki Takahashi, Nobuyuki Yamamoto, Fumiaki Koizumi, Yasuhiro Koh |
| Abstract |
Personalized cancer treatment relies on the accurate detection of actionable genomic aberrations in tumor cells. Circulating tumor cells (CTCs) could provide an alternative genetic resource for diagnosis; however, the technical difficulties in isolating and analyzing rare CTCs have limited progress to date. In this preclinical study, we aimed to develop an improved capture system for molecular characterization of CTCs based on a novel cell sorting technology. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 2% |
| France | 1 | 2% |
| Unknown | 57 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 24% |
| Researcher | 14 | 24% |
| Student > Master | 8 | 14% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 3 | 5% |
| Other | 7 | 12% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 31% |
| Medicine and Dentistry | 12 | 20% |
| Engineering | 7 | 12% |
| Biochemistry, Genetics and Molecular Biology | 5 | 8% |
| Chemistry | 2 | 3% |
| Other | 0 | 0% |
| Unknown | 15 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 18 August 2016.
All research outputs
#6,030,127
of 22,756,196 outputs
Outputs from Journal of Translational Medicine
#902
of 3,978 outputs
Outputs of similar age
#57,174
of 226,329 outputs
Outputs of similar age from Journal of Translational Medicine
#10
of 68 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 3,978 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 77% 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 226,329 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 74% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.