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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The complexity of gene expression dynamics revealed by permutation entropy
|
|---|---|
| Published in |
BMC Bioinformatics, December 2010
|
| DOI | 10.1186/1471-2105-11-607 |
| Pubmed ID | |
| Authors |
Xiaoliang Sun, Yong Zou, Victoria Nikiforova, Jürgen Kurths, Dirk Walther |
| Abstract |
High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. |
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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| United Kingdom | 3 | 4% |
| Germany | 2 | 3% |
| Italy | 1 | 1% |
| Portugal | 1 | 1% |
| Chile | 1 | 1% |
| Israel | 1 | 1% |
| Unknown | 60 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 33% |
| Researcher | 23 | 32% |
| Student > Master | 6 | 8% |
| Student > Doctoral Student | 4 | 5% |
| Student > Bachelor | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 2 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 38 | 52% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Computer Science | 7 | 10% |
| Engineering | 5 | 7% |
| Physics and Astronomy | 4 | 5% |
| Other | 7 | 10% |
| Unknown | 4 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 15 February 2015.
All research outputs
#18,399,793
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#6,311
of 7,280 outputs
Outputs of similar age
#161,648
of 182,042 outputs
Outputs of similar age from BMC Bioinformatics
#42
of 53 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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 182,042 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.