| Title |
De novo Nanopore read quality improvement using deep learning
|
|---|---|
| Published in |
BMC Bioinformatics, November 2019
|
| DOI | 10.1186/s12859-019-3103-z |
| Pubmed ID | |
| Authors |
Nathan LaPierre, Rob Egan, Wei Wang, Zhong Wang |
X Demographics
The data shown below were collected from the profiles of 21 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 | 5 | 24% |
| United Kingdom | 3 | 14% |
| Netherlands | 2 | 10% |
| France | 2 | 10% |
| Brazil | 1 | 5% |
| Germany | 1 | 5% |
| Spain | 1 | 5% |
| Unknown | 6 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 57% |
| Scientists | 9 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 20% |
| Researcher | 13 | 16% |
| Student > Master | 10 | 13% |
| Student > Bachelor | 6 | 8% |
| Other | 5 | 6% |
| Other | 9 | 11% |
| Unknown | 20 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 18 | 23% |
| Agricultural and Biological Sciences | 15 | 19% |
| Computer Science | 7 | 9% |
| Nursing and Health Professions | 3 | 4% |
| Medicine and Dentistry | 3 | 4% |
| Other | 9 | 11% |
| Unknown | 24 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 18 October 2021.
All research outputs
#3,563,369
of 25,138,857 outputs
Outputs from BMC Bioinformatics
#1,198
of 7,654 outputs
Outputs of similar age
#71,662
of 373,609 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 165 outputs
Altmetric has tracked 25,138,857 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,654 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 84% 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 373,609 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 80% of its contemporaries.
We're also able to compare this research output to 165 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.