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Attention Score in Context
| Title |
Independent component analysis of Alzheimer's DNA microarray gene expression data
|
|---|---|
| Published in |
Molecular Neurodegeneration, January 2009
|
| DOI | 10.1186/1750-1326-4-5 |
| Pubmed ID | |
| Authors |
Wei Kong, Xiaoyang Mou, Qingzhong Liu, Zhongxue Chen, Charles R Vanderburg, Jack T Rogers, Xudong Huang |
| Abstract |
Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA) and independent component analysis (ICA) have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 2% |
| Germany | 1 | 2% |
| Korea, Republic of | 1 | 2% |
| Unknown | 58 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 23% |
| Researcher | 13 | 21% |
| Student > Master | 11 | 18% |
| Student > Bachelor | 4 | 7% |
| Student > Doctoral Student | 2 | 3% |
| Other | 7 | 11% |
| Unknown | 10 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 39% |
| Biochemistry, Genetics and Molecular Biology | 10 | 16% |
| Computer Science | 5 | 8% |
| Neuroscience | 4 | 7% |
| Mathematics | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 10 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 April 2022.
All research outputs
#4,693,443
of 23,493,900 outputs
Outputs from Molecular Neurodegeneration
#543
of 871 outputs
Outputs of similar age
#26,320
of 174,188 outputs
Outputs of similar age from Molecular Neurodegeneration
#6
of 12 outputs
Altmetric has tracked 23,493,900 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 871 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 37th percentile – i.e., 37% 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 174,188 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.