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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DNA-based watermarks using the DNA-Crypt algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, May 2007
|
| DOI | 10.1186/1471-2105-8-176 |
| Pubmed ID | |
| Authors |
Dominik Heider, Angelika Barnekow |
| Abstract |
The aim of this paper is to demonstrate the application of watermarks based on DNA sequences to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. Predicted mutations in the genome can be corrected by the DNA-Crypt program leaving the encrypted information intact. Existing DNA cryptographic and steganographic algorithms use synthetic DNA sequences to store binary information however, although these sequences can be used for authentication, they may change the target DNA sequence when introduced into living organisms. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 6% |
| Russia | 2 | 3% |
| South Africa | 1 | 1% |
| Australia | 1 | 1% |
| Egypt | 1 | 1% |
| Unknown | 58 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 33% |
| Researcher | 13 | 19% |
| Student > Master | 7 | 10% |
| Student > Bachelor | 5 | 7% |
| Professor | 4 | 6% |
| Other | 6 | 9% |
| Unknown | 10 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 24% |
| Computer Science | 14 | 21% |
| Biochemistry, Genetics and Molecular Biology | 9 | 13% |
| Engineering | 5 | 7% |
| Physics and Astronomy | 4 | 6% |
| Other | 8 | 12% |
| Unknown | 11 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 03 October 2019.
All research outputs
#3,601,961
of 22,663,969 outputs
Outputs from BMC Bioinformatics
#1,335
of 7,247 outputs
Outputs of similar age
#10,441
of 70,708 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 50 outputs
Altmetric has tracked 22,663,969 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,247 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 81% 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 70,708 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 85% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.