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 |
An integrated hierarchical Bayesian approach to normalizing left-censored microRNA microarray data
|
|---|---|
| Published in |
BMC Genomics, July 2013
|
| DOI | 10.1186/1471-2164-14-507 |
| Pubmed ID | |
| Authors |
Jia Kang, Ethan Yixun Xu |
| Abstract |
MicroRNAs (miRNAs) are small endogenous ssRNAs that regulate target gene expression post-transcriptionally through the RNAi pathway. A critical pre-processing procedure for detecting differentially expressed miRNAs is normalization, aiming at removing the between-array systematic bias. Most normalization methods adopted for miRNA data are the same methods used to normalize mRNA data; but miRNA data are very different from mRNA data mainly because of possibly larger proportion of differentially expressed miRNA probes, and much larger percentage of left-censored miRNA probes below detection limit (DL). Taking the unique characteristics of miRNA data into account, we present a hierarchical Bayesian approach that integrates normalization, missing data imputation, and feature selection in the same model. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 12% |
| United Kingdom | 1 | 6% |
| Denmark | 1 | 6% |
| Unknown | 13 | 76% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 41% |
| Student > Ph. D. Student | 4 | 24% |
| Professor | 2 | 12% |
| Student > Master | 2 | 12% |
| Other | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 35% |
| Biochemistry, Genetics and Molecular Biology | 3 | 18% |
| Mathematics | 2 | 12% |
| Computer Science | 2 | 12% |
| Medicine and Dentistry | 2 | 12% |
| Other | 1 | 6% |
| Unknown | 1 | 6% |
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 06 August 2013.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from BMC Genomics
#8,709
of 11,244 outputs
Outputs of similar age
#159,591
of 209,852 outputs
Outputs of similar age from BMC Genomics
#128
of 175 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. 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 209,852 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 175 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.