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A multivariate approach to the integration of multi-omics datasets

Overview of attention for article published in BMC Bioinformatics, May 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

twitter
27 X users
facebook
2 Facebook pages
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
239 Dimensions

Readers on

mendeley
528 Mendeley
citeulike
8 CiteULike
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Title
A multivariate approach to the integration of multi-omics datasets
Published in
BMC Bioinformatics, May 2014
DOI 10.1186/1471-2105-15-162
Pubmed ID
Authors

Chen Meng, Bernhard Kuster, Aedín C Culhane, Amin Moghaddas Gholami

Abstract

To leverage the potential of multi-omics studies, exploratory data analysis methods that provide systematic integration and comparison of multiple layers of omics information are required. We describe multiple co-inertia analysis (MCIA), an exploratory data analysis method that identifies co-relationships between multiple high dimensional datasets. Based on a covariance optimization criterion, MCIA simultaneously projects several datasets into the same dimensional space, transforming diverse sets of features onto the same scale, to extract the most variant from each dataset and facilitate biological interpretation and pathway analysis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 528 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%
United Kingdom 4 <1%
Sweden 3 <1%
Netherlands 3 <1%
Brazil 2 <1%
Italy 2 <1%
Belgium 2 <1%
Portugal 2 <1%
Other 7 1%
Unknown 490 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 147 28%
Researcher 130 25%
Student > Master 40 8%
Student > Bachelor 38 7%
Student > Doctoral Student 20 4%
Other 73 14%
Unknown 80 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 160 30%
Biochemistry, Genetics and Molecular Biology 95 18%
Computer Science 59 11%
Medicine and Dentistry 22 4%
Mathematics 21 4%
Other 66 13%
Unknown 105 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 11 June 2023.
All research outputs
#1,988,099
of 24,598,501 outputs
Outputs from BMC Bioinformatics
#460
of 7,559 outputs
Outputs of similar age
#19,689
of 231,414 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 154 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,559 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 done particularly well, scoring higher than 93% 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 231,414 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 154 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.