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X Demographics
Mendeley readers
Attention Score in Context
Title |
Space-efficient and exact de Bruijn graph representation based on a Bloom filter
|
---|---|
Published in |
Algorithms for Molecular Biology, September 2013
|
DOI | 10.1186/1748-7188-8-22 |
Pubmed ID | |
Authors |
Rayan Chikhi, Guillaume Rizk |
Abstract |
The de Bruijn graph data structure is widely used in next-generation sequencing (NGS). Many programs, e.g. de novo assemblers, rely on in-memory representation of this graph. However, current techniques for representing the de Bruijn graph of a human genome require a large amount of memory (≥30 GB). |
X Demographics
The data shown below were collected from the profiles of 15 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 | 2 | 13% |
Canada | 1 | 7% |
Sweden | 1 | 7% |
Norway | 1 | 7% |
United Kingdom | 1 | 7% |
Germany | 1 | 7% |
India | 1 | 7% |
Unknown | 7 | 47% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 53% |
Scientists | 7 | 47% |
Mendeley readers
The data shown below were compiled from readership statistics for 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 3% |
France | 4 | 2% |
Germany | 2 | <1% |
Bulgaria | 1 | <1% |
Vietnam | 1 | <1% |
Australia | 1 | <1% |
Brazil | 1 | <1% |
Korea, Republic of | 1 | <1% |
South Africa | 1 | <1% |
Other | 3 | 1% |
Unknown | 196 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 53 | 24% |
Researcher | 40 | 18% |
Student > Master | 34 | 16% |
Student > Bachelor | 18 | 8% |
Student > Doctoral Student | 13 | 6% |
Other | 34 | 16% |
Unknown | 25 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 74 | 34% |
Computer Science | 56 | 26% |
Biochemistry, Genetics and Molecular Biology | 36 | 17% |
Engineering | 5 | 2% |
Immunology and Microbiology | 5 | 2% |
Other | 14 | 6% |
Unknown | 27 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 32. 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 13 February 2024.
All research outputs
#1,078,165
of 23,073,835 outputs
Outputs from Algorithms for Molecular Biology
#2
of 264 outputs
Outputs of similar age
#9,326
of 180,276 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 4 outputs
Altmetric has tracked 23,073,835 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 264 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 99% 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 180,276 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 94% of its contemporaries.
We're also able to compare this research output to 4 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