↓ Skip to main content

Implications of non-uniqueness in phylogenetic deconvolution of bulk DNA samples of tumors

Overview of attention for article published in Algorithms for Molecular Biology, September 2019
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#24 of 264)
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog
twitter
2 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
10 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Implications of non-uniqueness in phylogenetic deconvolution of bulk DNA samples of tumors
Published in
Algorithms for Molecular Biology, September 2019
DOI 10.1186/s13015-019-0155-6
Pubmed ID
Authors

Yuanyuan Qi, Dikshant Pradhan, Mohammed El-Kebir

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 20%
Professor 1 10%
Student > Ph. D. Student 1 10%
Researcher 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 4 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 20%
Agricultural and Biological Sciences 2 20%
Mathematics 1 10%
Computer Science 1 10%
Engineering 1 10%
Other 0 0%
Unknown 3 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 September 2019.
All research outputs
#3,739,646
of 23,155,957 outputs
Outputs from Algorithms for Molecular Biology
#24
of 264 outputs
Outputs of similar age
#73,540
of 340,326 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 5 outputs
Altmetric has tracked 23,155,957 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done particularly well, scoring higher than 90% 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 340,326 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 5 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