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Attention Score in Context
Title |
More Is Better: Recent Progress in Multi-Omics Data Integration Methods
|
---|---|
Published in |
Frontiers in Genetics, June 2017
|
DOI | 10.3389/fgene.2017.00084 |
Pubmed ID | |
Authors |
Sijia Huang, Kumardeep Chaudhary, Lana X. Garmire |
Abstract |
Multi-omics data integration is one of the major challenges in the era of precision medicine. Considerable work has been done with the advent of high-throughput studies, which have enabled the data access for downstream analyses. To improve the clinical outcome prediction, a gamut of software tools has been developed. This review outlines the progress done in the field of multi-omics integration and comprehensive tools developed so far in this field. Further, we discuss the integration methods to predict patient survival at the end of the review. |
X Demographics
The data shown below were collected from the profiles of 81 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 | 9 | 11% |
Spain | 5 | 6% |
South Africa | 3 | 4% |
Switzerland | 3 | 4% |
India | 3 | 4% |
Mexico | 2 | 2% |
Venezuela, Bolivarian Republic of | 2 | 2% |
United Kingdom | 2 | 2% |
Indonesia | 1 | 1% |
Other | 12 | 15% |
Unknown | 39 | 48% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 52 | 64% |
Scientists | 24 | 30% |
Practitioners (doctors, other healthcare professionals) | 5 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,048 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Norway | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 1045 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 242 | 23% |
Researcher | 213 | 20% |
Student > Master | 107 | 10% |
Student > Bachelor | 66 | 6% |
Student > Doctoral Student | 48 | 5% |
Other | 145 | 14% |
Unknown | 227 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 260 | 25% |
Agricultural and Biological Sciences | 177 | 17% |
Computer Science | 119 | 11% |
Medicine and Dentistry | 42 | 4% |
Engineering | 37 | 4% |
Other | 136 | 13% |
Unknown | 277 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 95. 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 20 June 2023.
All research outputs
#455,473
of 25,736,439 outputs
Outputs from Frontiers in Genetics
#64
of 13,784 outputs
Outputs of similar age
#9,151
of 318,228 outputs
Outputs of similar age from Frontiers in Genetics
#2
of 50 outputs
Altmetric has tracked 25,736,439 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,784 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 99% 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 318,228 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 97% of its contemporaries.
We're also able to compare this research output to 50 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 96% of its contemporaries.