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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Analysis of nanopore data using hidden Markov models
|
|---|---|
| Published in |
Bioinformatics, February 2015
|
| DOI | 10.1093/bioinformatics/btv046 |
| Pubmed ID | |
| Authors |
Jacob Schreiber, Kevin Karplus |
| Abstract |
Nanopore-based sequencing techniques can reconstruct properties of biosequences by analyzing the sequence-dependent ionic current steps produced as biomolecules pass through a pore. Typically this involves alignment of new data to a reference, where both reference construction and alignment have been performed by hand. |
X Demographics
The data shown below were collected from the profiles of 30 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 | 10 | 33% |
| United Kingdom | 4 | 13% |
| Norway | 2 | 7% |
| India | 2 | 7% |
| France | 2 | 7% |
| Germany | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 8 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 21 | 70% |
| Members of the public | 9 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| Switzerland | 1 | 1% |
| Netherlands | 1 | 1% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Sweden | 1 | 1% |
| Czechia | 1 | 1% |
| United Kingdom | 1 | 1% |
| New Zealand | 1 | 1% |
| Other | 3 | 3% |
| Unknown | 81 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 31% |
| Researcher | 18 | 19% |
| Student > Bachelor | 11 | 12% |
| Student > Master | 11 | 12% |
| Student > Doctoral Student | 4 | 4% |
| Other | 13 | 14% |
| Unknown | 8 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 34% |
| Biochemistry, Genetics and Molecular Biology | 15 | 16% |
| Computer Science | 15 | 16% |
| Engineering | 6 | 6% |
| Chemistry | 5 | 5% |
| Other | 7 | 7% |
| Unknown | 14 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 23 February 2021.
All research outputs
#2,130,497
of 25,373,627 outputs
Outputs from Bioinformatics
#1,373
of 12,808 outputs
Outputs of similar age
#29,235
of 360,613 outputs
Outputs of similar age from Bioinformatics
#30
of 191 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 89% 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 360,613 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 91% of its contemporaries.
We're also able to compare this research output to 191 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.