Title |
geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification
|
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Published in |
BMC Bioinformatics, January 2014
|
DOI | 10.1186/1471-2105-15-31 |
Pubmed ID | |
Authors |
Miguel Reboiro-Jato, Joel P Arrais, José Luis Oliveira, Florentino Fdez-Riverola |
Abstract |
The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 14% |
Norway | 1 | 14% |
Spain | 1 | 14% |
Unknown | 4 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 4 | 57% |
Members of the public | 2 | 29% |
Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 3% |
Unknown | 35 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 19% |
Librarian | 6 | 17% |
Other | 5 | 14% |
Student > Bachelor | 5 | 14% |
Professor > Associate Professor | 4 | 11% |
Other | 7 | 19% |
Unknown | 2 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 28% |
Medicine and Dentistry | 8 | 22% |
Agricultural and Biological Sciences | 6 | 17% |
Engineering | 2 | 6% |
Chemistry | 2 | 6% |
Other | 2 | 6% |
Unknown | 6 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 22 June 2015.
All research outputs
#6,695,536
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#2,512
of 7,454 outputs
Outputs of similar age
#77,730
of 313,202 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 96 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 66% 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 313,202 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 75% of its contemporaries.
We're also able to compare this research output to 96 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 72% of its contemporaries.