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Mendeley readers
Attention Score in Context
| Title |
The fractal based analysis of human face and DNA variations during aging
|
|---|---|
| Published in |
BioScience Trends, October 2016
|
| DOI | 10.5582/bst.2016.01182 |
| Pubmed ID | |
| Authors |
Hamidreza Namazi, Amin Akrami, Jamal Hussaini, Osmar N. Silva, Albert Wong, Vladimir V. Kulish |
| Abstract |
Human DNA is the main unit that shapes human characteristics and features such as behavior. Thus, it is expected that changes in DNA (DNA mutation) influence human characteristics and features. Face is one of the human features which is unique and also dependent on his gen. In this paper, for the first time we analyze the variations of human DNA and face simultaneously. We do this job by analyzing the fractal dimension of DNA walk and face during human aging. The results of this study show the human DNA and face get more complex by aging. These complexities are mapped on fractal exponents of DNA walk and human face. The method discussed in this paper can be further developed in order to investigate the direct influence of DNA mutation on the face variations during aging, and accordingly making a model between human face fractality and the complexity of DNA walk. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 18% |
| Professor > Associate Professor | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Student > Bachelor | 1 | 9% |
| Researcher | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 2 | 18% |
| Veterinary Science and Veterinary Medicine | 1 | 9% |
| Computer Science | 1 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Medicine and Dentistry | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 4 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 30 July 2017.
All research outputs
#15,168,964
of 25,371,288 outputs
Outputs from BioScience Trends
#97
of 333 outputs
Outputs of similar age
#174,841
of 319,604 outputs
Outputs of similar age from BioScience Trends
#1
of 1 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 333 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.9. This one has gotten more attention than average, scoring higher than 68% 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 319,604 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them