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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A novel regulatory event-based gene set analysis method for exploring global functional changes in heterogeneous genomic data sets
|
|---|---|
| Published in |
BMC Genomics, January 2009
|
| DOI | 10.1186/1471-2164-10-26 |
| Pubmed ID | |
| Authors |
Chien-Yi Tung, Chih-Hung Jen, Ming-Ta Hsu, Hsei-Wei Wang, Chi-Hung Lin |
| Abstract |
Analyzing gene expression data by assessing the significance of pre-defined gene sets, rather than individual genes, has become a main approach in microarray data analysis and this has promisingly derive new biological interpretations of microarray data. However, the detection power of conventional gene list or gene set-based approaches is limited on highly heterogeneous samples, such as tumors. |
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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 7% |
| Italy | 1 | 7% |
| Unknown | 13 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 40% |
| Student > Ph. D. Student | 4 | 27% |
| Professor > Associate Professor | 2 | 13% |
| Student > Master | 1 | 7% |
| Professor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 40% |
| Medicine and Dentistry | 4 | 27% |
| Computer Science | 2 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 13% |
| Unknown | 1 | 7% |
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 03 May 2012.
All research outputs
#18,305,773
of 22,664,644 outputs
Outputs from BMC Genomics
#8,144
of 10,615 outputs
Outputs of similar age
#158,285
of 169,879 outputs
Outputs of similar age from BMC Genomics
#118
of 127 outputs
Altmetric has tracked 22,664,644 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 10,615 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 169,879 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.