You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Missing value imputation for microarray data: a comprehensive comparison study and a web tool
|
|---|---|
| Published in |
BMC Systems Biology, December 2013
|
| DOI | 10.1186/1752-0509-7-s6-s12 |
| Pubmed ID | |
| Authors |
Chia-Chun Chiu, Shih-Yao Chan, Chung-Ching Wang, Wei-Sheng Wu |
| Abstract |
Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 2% |
| Taiwan | 1 | 2% |
| Unknown | 41 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 23% |
| Researcher | 8 | 19% |
| Student > Bachelor | 5 | 12% |
| Other | 3 | 7% |
| Student > Master | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 11 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 26% |
| Agricultural and Biological Sciences | 6 | 14% |
| Biochemistry, Genetics and Molecular Biology | 3 | 7% |
| Engineering | 3 | 7% |
| Medicine and Dentistry | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 14 | 33% |
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 19 November 2021.
All research outputs
#15,309,583
of 22,769,322 outputs
Outputs from BMC Systems Biology
#644
of 1,142 outputs
Outputs of similar age
#192,669
of 307,487 outputs
Outputs of similar age from BMC Systems Biology
#34
of 61 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 32nd percentile – i.e., 32% 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 307,487 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.