↓ Skip to main content

DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics

Overview of attention for article published in Molecular Autism, March 2014
Altmetric Badge

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 (99th percentile)

Mentioned by

blogs
2 blogs
twitter
6 tweeters
patent
1 patent
facebook
1 Facebook page

Citations

dimensions_citation
95 Dimensions

Readers on

mendeley
178 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics
Published in
Molecular Autism, March 2014
DOI 10.1186/2040-2392-5-22
Pubmed ID
Authors

Li Liu, Jing Lei, Stephan J Sanders, Arthur Jeremy Willsey, Yan Kou, Abdullah Ercument Cicek, Lambertus Klei, Cong Lu, Xin He, Mingfeng Li, Rebecca A Muhle, Avi Ma’ayan, James P Noonan, Nenad Šestan, Kathryn A McFadden, Matthew W State, Joseph D Buxbaum, Bernie Devlin, Kathryn Roeder

Abstract

De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Germany 2 1%
Italy 1 <1%
Netherlands 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
China 1 <1%
Portugal 1 <1%
Unknown 165 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 26%
Student > Ph. D. Student 41 23%
Student > Master 16 9%
Student > Bachelor 15 8%
Professor 14 8%
Other 25 14%
Unknown 21 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 35%
Biochemistry, Genetics and Molecular Biology 35 20%
Medicine and Dentistry 15 8%
Neuroscience 14 8%
Computer Science 8 4%
Other 15 8%
Unknown 29 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 April 2019.
All research outputs
#1,246,019
of 17,361,274 outputs
Outputs from Molecular Autism
#145
of 573 outputs
Outputs of similar age
#15,715
of 194,441 outputs
Outputs of similar age from Molecular Autism
#1
of 15 outputs
Altmetric has tracked 17,361,274 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 573 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.7. This one has gotten more attention than average, scoring higher than 74% 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 194,441 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 15 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 99% of its contemporaries.