↓ Skip to main content

A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data

Overview of attention for article published in BioData Mining, July 2012
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
91 Mendeley
citeulike
1 CiteULike
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.
Title
A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data
Published in
BioData Mining, July 2012
DOI 10.1186/1756-0381-5-8
Pubmed ID
Authors

Li, Yang Guo, Wenwu Wu, Youyi Shi, Jian Cheng, Shiheng Tao

Abstract

Several biclustering algorithms have been proposed to identify biclusters, in which genes share similar expression patterns across a number of conditions. However, different algorithms would yield different biclusters and further lead to distinct conclusions. Therefore, some testing and comparisons between these algorithms are strongly required.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Italy 1 1%
Cuba 1 1%
Sweden 1 1%
Finland 1 1%
China 1 1%
Japan 1 1%
United States 1 1%
Unknown 83 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 29%
Student > Ph. D. Student 24 26%
Student > Master 9 10%
Student > Postgraduate 6 7%
Student > Doctoral Student 5 5%
Other 16 18%
Unknown 5 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 31%
Computer Science 27 30%
Biochemistry, Genetics and Molecular Biology 10 11%
Medicine and Dentistry 3 3%
Mathematics 3 3%
Other 12 13%
Unknown 8 9%

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 25 August 2012.
All research outputs
#2,711,084
of 11,326,849 outputs
Outputs from BioData Mining
#90
of 209 outputs
Outputs of similar age
#24,705
of 109,075 outputs
Outputs of similar age from BioData Mining
#4
of 5 outputs
Altmetric has tracked 11,326,849 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 209 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 56% 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 109,075 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 77% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.