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Deep Sequencing Data Analysis

Overview of attention for book
Attention for Chapter: Applications of Community Detection Algorithms to Large Biological Datasets
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Citations

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1 Dimensions

Readers on

mendeley
26 Mendeley
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Chapter title
Applications of Community Detection Algorithms to Large Biological Datasets
Book title
Deep Sequencing Data Analysis
Published in
Methods in molecular biology, July 2020
DOI 10.1007/978-1-0716-1103-6_3
Pubmed ID
Book ISBNs
978-1-07-161102-9, 978-1-07-161103-6
Authors

Itamar Kanter, Gur Yaari, Tomer Kalisky, Kanter, Itamar, Yaari, Gur, Kalisky, Tomer

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Researcher 4 15%
Student > Master 4 15%
Professor > Associate Professor 3 12%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 8 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 23%
Biochemistry, Genetics and Molecular Biology 3 12%
Computer Science 3 12%
Neuroscience 2 8%
Immunology and Microbiology 1 4%
Other 3 12%
Unknown 8 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 February 2021.
All research outputs
#15,681,103
of 23,302,246 outputs
Outputs from Methods in molecular biology
#5,494
of 13,338 outputs
Outputs of similar age
#249,717
of 399,359 outputs
Outputs of similar age from Methods in molecular biology
#88
of 207 outputs
Altmetric has tracked 23,302,246 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,338 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 399,359 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 207 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.