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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets
|
|---|---|
| Published in |
BMC Bioinformatics, February 2012
|
| DOI | 10.1186/1471-2105-13-24 |
| Pubmed ID | |
| Authors |
Fangzhou Yao, Jeff Coquery, Kim-Anh Lê Cao |
| Abstract |
A key question when analyzing high throughput data is whether the information provided by the measured biological entities (gene, metabolite expression for example) is related to the experimental conditions, or, rather, to some interfering signals, such as experimental bias or artefacts. Visualization tools are therefore useful to better understand the underlying structure of the data in a 'blind' (unsupervised) way. A well-established technique to do so is Principal Component Analysis (PCA). PCA is particularly powerful if the biological question is related to the highest variance. Independent Component Analysis (ICA) has been proposed as an alternative to PCA as it optimizes an independence condition to give more meaningful components. However, neither PCA nor ICA can overcome both the high dimensionality and noisy characteristics of biological data. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 3 | 23% |
| United States | 3 | 23% |
| Australia | 2 | 15% |
| United Kingdom | 2 | 15% |
| Colombia | 1 | 8% |
| Malaysia | 1 | 8% |
| Unknown | 1 | 8% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 62% |
| Members of the public | 5 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 375 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 2% |
| Germany | 4 | 1% |
| Portugal | 3 | <1% |
| Canada | 3 | <1% |
| Sweden | 2 | <1% |
| United Kingdom | 2 | <1% |
| Norway | 1 | <1% |
| France | 1 | <1% |
| Malaysia | 1 | <1% |
| Other | 6 | 2% |
| Unknown | 343 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 93 | 25% |
| Researcher | 77 | 21% |
| Student > Master | 46 | 12% |
| Other | 23 | 6% |
| Student > Bachelor | 21 | 6% |
| Other | 59 | 16% |
| Unknown | 56 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 130 | 35% |
| Biochemistry, Genetics and Molecular Biology | 50 | 13% |
| Engineering | 21 | 6% |
| Computer Science | 20 | 5% |
| Medicine and Dentistry | 12 | 3% |
| Other | 71 | 19% |
| Unknown | 71 | 19% |
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 08 October 2019.
All research outputs
#4,805,073
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,803
of 7,400 outputs
Outputs of similar age
#41,997
of 251,254 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 57 outputs
Altmetric has tracked 23,577,654 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 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% of its peers.
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 251,254 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 83% of its contemporaries.
We're also able to compare this research output to 57 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 73% of its contemporaries.