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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution
|
|---|---|
| Published in |
PLoS Computational Biology, August 2014
|
| DOI | 10.1371/journal.pcbi.1003665 |
| Pubmed ID | |
| Authors |
Christopher A. Miller, Brian S. White, Nathan D. Dees, Malachi Griffith, John S. Welch, Obi L. Griffith, Ravi Vij, Michael H. Tomasson, Timothy A. Graubert, Matthew J. Walter, Matthew J. Ellis, William Schierding, John F. DiPersio, Timothy J. Ley, Elaine R. Mardis, Richard K. Wilson, Li Ding |
X Demographics
The data shown below were collected from the profiles of 36 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 | 20 | 56% |
| Canada | 3 | 8% |
| Argentina | 1 | 3% |
| Montenegro | 1 | 3% |
| Switzerland | 1 | 3% |
| Spain | 1 | 3% |
| Sweden | 1 | 3% |
| Unknown | 8 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 23 | 64% |
| Members of the public | 12 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 483 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 12 | 2% |
| United Kingdom | 4 | <1% |
| Italy | 4 | <1% |
| Germany | 3 | <1% |
| China | 2 | <1% |
| Canada | 2 | <1% |
| Korea, Republic of | 1 | <1% |
| Australia | 1 | <1% |
| Norway | 1 | <1% |
| Other | 8 | 2% |
| Unknown | 445 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 119 | 25% |
| Student > Ph. D. Student | 112 | 23% |
| Student > Bachelor | 38 | 8% |
| Student > Master | 35 | 7% |
| Student > Doctoral Student | 31 | 6% |
| Other | 72 | 15% |
| Unknown | 76 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 153 | 32% |
| Biochemistry, Genetics and Molecular Biology | 118 | 24% |
| Computer Science | 50 | 10% |
| Medicine and Dentistry | 43 | 9% |
| Mathematics | 11 | 2% |
| Other | 26 | 5% |
| Unknown | 82 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 36. 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 03 October 2023.
All research outputs
#1,134,182
of 25,837,817 outputs
Outputs from PLoS Computational Biology
#901
of 9,035 outputs
Outputs of similar age
#11,016
of 243,500 outputs
Outputs of similar age from PLoS Computational Biology
#12
of 163 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,035 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 89% 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 243,500 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.