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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Methods for the integration of multi-omics data: mathematical aspects
|
|---|---|
| Published in |
BMC Bioinformatics, January 2016
|
| DOI | 10.1186/s12859-015-0857-9 |
| Pubmed ID | |
| Authors |
Matteo Bersanelli, Ettore Mosca, Daniel Remondini, Enrico Giampieri, Claudia Sala, Gastone Castellani, Luciano Milanesi |
| Abstract |
Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| India | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 849 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | <1% |
| Canada | 2 | <1% |
| Brazil | 2 | <1% |
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| Sweden | 1 | <1% |
| United Kingdom | 1 | <1% |
| Germany | 1 | <1% |
| Argentina | 1 | <1% |
| Other | 3 | <1% |
| Unknown | 831 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 217 | 26% |
| Researcher | 159 | 19% |
| Student > Master | 99 | 12% |
| Student > Bachelor | 58 | 7% |
| Student > Postgraduate | 35 | 4% |
| Other | 131 | 15% |
| Unknown | 150 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 202 | 24% |
| Agricultural and Biological Sciences | 162 | 19% |
| Computer Science | 106 | 12% |
| Medicine and Dentistry | 37 | 4% |
| Engineering | 36 | 4% |
| Other | 118 | 14% |
| Unknown | 188 | 22% |
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 06 September 2023.
All research outputs
#5,284,655
of 25,837,817 outputs
Outputs from BMC Bioinformatics
#1,820
of 7,763 outputs
Outputs of similar age
#83,861
of 407,136 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 147 outputs
Altmetric has tracked 25,837,817 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 7,763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 76% 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 407,136 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 79% of its contemporaries.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.