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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithm
|
|---|---|
| Published in |
BMC Bioinformatics, February 2014
|
| DOI | 10.1186/1471-2105-15-49 |
| Pubmed ID | |
| Authors |
Kun-Huang Chen, Kung-Jeng Wang, Min-Lung Tsai, Kung-Min Wang, Angelia Melani Adrian, Wei-Chung Cheng, Tzu-Sen Yang, Nai-Chia Teng, Kuo-Pin Tan, Ku-Shang Chang |
| Abstract |
In the application of microarray data, how to select a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers is an important issue. Many researchers use various computational intelligence methods to analyzed gene expression data. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| Sweden | 1 | 25% |
| Norway | 1 | 25% |
| Japan | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hong Kong | 1 | <1% |
| Cuba | 1 | <1% |
| Netherlands | 1 | <1% |
| Sweden | 1 | <1% |
| Unknown | 114 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 22 | 19% |
| Student > Ph. D. Student | 18 | 15% |
| Researcher | 15 | 13% |
| Student > Bachelor | 12 | 10% |
| Lecturer | 6 | 5% |
| Other | 18 | 15% |
| Unknown | 27 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 37 | 31% |
| Engineering | 15 | 13% |
| Agricultural and Biological Sciences | 12 | 10% |
| Biochemistry, Genetics and Molecular Biology | 7 | 6% |
| Medicine and Dentistry | 4 | 3% |
| Other | 11 | 9% |
| Unknown | 32 | 27% |
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 18 March 2014.
All research outputs
#13,910,091
of 22,745,803 outputs
Outputs from BMC Bioinformatics
#4,473
of 7,268 outputs
Outputs of similar age
#117,930
of 224,154 outputs
Outputs of similar age from BMC Bioinformatics
#62
of 109 outputs
Altmetric has tracked 22,745,803 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,268 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 35th percentile – i.e., 35% 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 224,154 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.