Title |
Stepwise large genome assembly approach: a case of Siberian larch (Larix sibirica Ledeb)
|
---|---|
Published in |
BMC Bioinformatics, February 2019
|
DOI | 10.1186/s12859-018-2570-y |
Pubmed ID | |
Authors |
Dmitry A. Kuzmin, Sergey I. Feranchuk, Vadim V. Sharov, Alexander N. Cybin, Stepan V. Makolov, Yuliya A. Putintseva, Natalya V. Oreshkova, Konstantin V. Krutovsky |
X Demographics
The data shown below were collected from the profiles of 8 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 | 38% |
India | 2 | 25% |
New Zealand | 1 | 13% |
United States | 1 | 13% |
Unknown | 1 | 13% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 5 | 63% |
Members of the public | 3 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 42 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 17 | 40% |
Student > Master | 7 | 17% |
Researcher | 5 | 12% |
Student > Bachelor | 3 | 7% |
Professor | 2 | 5% |
Other | 5 | 12% |
Unknown | 3 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 45% |
Biochemistry, Genetics and Molecular Biology | 8 | 19% |
Computer Science | 2 | 5% |
Medicine and Dentistry | 2 | 5% |
Economics, Econometrics and Finance | 1 | 2% |
Other | 1 | 2% |
Unknown | 9 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 29 July 2020.
All research outputs
#4,133,720
of 23,128,387 outputs
Outputs from BMC Bioinformatics
#1,582
of 7,335 outputs
Outputs of similar age
#95,162
of 437,501 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 180 outputs
Altmetric has tracked 23,128,387 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,335 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 done well, scoring higher than 78% 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 437,501 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 180 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.