| Title |
An integrative approach for building personalized gene regulatory networks for precision medicine
|
|---|---|
| Published in |
Genome Medicine, December 2018
|
| DOI | 10.1186/s13073-018-0608-4 |
| Pubmed ID | |
| Authors |
Monique G. P. van der Wijst, Dylan H. de Vries, Harm Brugge, Harm-Jan Westra, Lude Franke |
X Demographics
The data shown below were collected from the profiles of 48 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 | 11 | 23% |
| United Kingdom | 7 | 15% |
| Switzerland | 5 | 10% |
| Germany | 4 | 8% |
| Netherlands | 3 | 6% |
| Spain | 2 | 4% |
| Taiwan | 1 | 2% |
| Mexico | 1 | 2% |
| Canada | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 11 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 25 | 52% |
| Members of the public | 22 | 46% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 192 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 36 | 19% |
| Student > Ph. D. Student | 34 | 18% |
| Student > Master | 21 | 11% |
| Student > Bachelor | 16 | 8% |
| Student > Doctoral Student | 9 | 5% |
| Other | 23 | 12% |
| Unknown | 53 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 59 | 31% |
| Agricultural and Biological Sciences | 25 | 13% |
| Computer Science | 13 | 7% |
| Medicine and Dentistry | 10 | 5% |
| Engineering | 6 | 3% |
| Other | 20 | 10% |
| Unknown | 59 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. 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 31 January 2019.
All research outputs
#1,470,734
of 25,779,988 outputs
Outputs from Genome Medicine
#312
of 1,613 outputs
Outputs of similar age
#32,675
of 446,666 outputs
Outputs of similar age from Genome Medicine
#6
of 26 outputs
Altmetric has tracked 25,779,988 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,613 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.1. This one has done well, scoring higher than 80% 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 446,666 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 92% of its contemporaries.
We're also able to compare this research output to 26 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.