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Mendeley readers
Attention Score in Context
Title |
A multivariate approach to the integration of multi-omics datasets
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Published in |
BMC Bioinformatics, May 2014
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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
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 22% |
Germany | 2 | 7% |
Ireland | 1 | 4% |
United Kingdom | 1 | 4% |
Guinea | 1 | 4% |
Poland | 1 | 4% |
Mexico | 1 | 4% |
Spain | 1 | 4% |
France | 1 | 4% |
Other | 0 | 0% |
Unknown | 12 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 19 | 70% |
Members of the public | 8 | 30% |
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
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.