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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CAISC: A software to integrate copy number variations and single nucleotide mutations for genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, March 2022
|
| DOI | 10.1186/s12859-022-04625-x |
| Pubmed ID | |
| Authors |
Jeerthi Kannan, Liza Mathews, Zhijie Wu, Neal S. Young, Shouguo Gao |
X Demographics
The data shown below were collected from the profiles of 12 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 Kingdom | 3 | 25% |
| India | 1 | 8% |
| Sweden | 1 | 8% |
| Spain | 1 | 8% |
| United States | 1 | 8% |
| Italy | 1 | 8% |
| Unknown | 4 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 14% |
| Student > Doctoral Student | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Student > Master | 1 | 7% |
| Researcher | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 6 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 36% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
| Business, Management and Accounting | 1 | 7% |
| Engineering | 1 | 7% |
| Unknown | 6 | 43% |
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 31 March 2022.
All research outputs
#6,358,283
of 23,460,553 outputs
Outputs from BMC Bioinformatics
#2,372
of 7,391 outputs
Outputs of similar age
#128,337
of 440,938 outputs
Outputs of similar age from BMC Bioinformatics
#25
of 110 outputs
Altmetric has tracked 23,460,553 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,391 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 67% 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 440,938 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 70% of its contemporaries.
We're also able to compare this research output to 110 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.