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X Demographics
Mendeley readers
Attention Score in Context
| Title |
BioCode: Two biologically compatible Algorithms for embedding data in non-coding and coding regions of DNA
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-121 |
| Pubmed ID | |
| Authors |
David Haughton, Félix Balado |
| Abstract |
In recent times, the application of deoxyribonucleic acid (DNA) has diversified with the emergence of fields such as DNA computing and DNA data embedding. DNA data embedding, also known as DNA watermarking or DNA steganography, aims to develop robust algorithms for encoding non-genetic information in DNA. Inherently DNA is a digital medium whereby the nucleotide bases act as digital symbols, a fact which underpins all bioinformatics techniques, and which also makes trivial information encoding using DNA straightforward. However, the situation is more complex in methods which aim at embedding information in the genomes of living organisms. DNA is susceptible to mutations, which act as a noisy channel from the point of view of information encoded using DNA. This means that the DNA data embedding field is closely related to digital communications. Moreover it is a particularly unique digital communications area, because important biological constraints must be observed by all methods. Many DNA data embedding algorithms have been presented to date, all of which operate in one of two regions: non-coding DNA (ncDNA) or protein-coding DNA (pcDNA). |
X Demographics
The data shown below were collected from the profiles of 22 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 | 6 | 27% |
| United Kingdom | 5 | 23% |
| India | 2 | 9% |
| Japan | 1 | 5% |
| Spain | 1 | 5% |
| Germany | 1 | 5% |
| Ireland | 1 | 5% |
| Belgium | 1 | 5% |
| Unknown | 4 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 64% |
| Scientists | 6 | 27% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Sweden | 1 | 2% |
| Russia | 1 | 2% |
| Unknown | 48 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 22% |
| Student > Master | 9 | 18% |
| Researcher | 7 | 14% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 29% |
| Computer Science | 7 | 14% |
| Biochemistry, Genetics and Molecular Biology | 6 | 12% |
| Engineering | 5 | 10% |
| Chemical Engineering | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 10 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 27 December 2020.
All research outputs
#1,698,526
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#349
of 7,454 outputs
Outputs of similar age
#14,078
of 201,575 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 137 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 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 particularly well, scoring higher than 95% 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 201,575 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 93% of its contemporaries.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.