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Towards a molecular characterization of autism spectrum disorders: an exome sequencing and systems approach

Overview of attention for article published in Translational Psychiatry, June 2014
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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 (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
7 X users

Citations

dimensions_citation
57 Dimensions

Readers on

mendeley
160 Mendeley
citeulike
1 CiteULike
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Title
Towards a molecular characterization of autism spectrum disorders: an exome sequencing and systems approach
Published in
Translational Psychiatry, June 2014
DOI 10.1038/tp.2014.38
Pubmed ID
Authors

J Y An, A S Cristino, Q Zhao, J Edson, S M Williams, D Ravine, J Wray, V M Marshall, A Hunt, A J O Whitehouse, C Claudianos

Abstract

The hypothetical 'AXAS' gene network model that profiles functional patterns of heterogeneous DNA variants overrepresented in autism spectrum disorder (ASD), X-linked intellectual disability, attention deficit and hyperactivity disorder and schizophrenia was used in this current study to analyze whole exome sequencing data from an Australian ASD cohort. An optimized DNA variant filtering pipeline was used to identify loss-of-function DNA variations. Inherited variants from parents with a broader autism phenotype and de novo variants were found to be significantly associated with ASD. Gene ontology analysis revealed that putative rare causal variants cluster in key neurobiological processes and are overrepresented in functions involving neuronal development, signal transduction and synapse development including the neurexin trans-synaptic complex. We also show how a complex gene network model can be used to fine map combinations of inherited and de novo variations in families with ASD that converge in the L1CAM pathway. Our results provide an important step forward in the molecular characterization of ASD with potential for developing a tool to analyze the pathogenesis of individual affected families.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 1%
Italy 1 <1%
Brazil 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 154 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 20%
Researcher 29 18%
Student > Master 25 16%
Student > Bachelor 14 9%
Professor 9 6%
Other 29 18%
Unknown 22 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 22%
Medicine and Dentistry 26 16%
Biochemistry, Genetics and Molecular Biology 23 14%
Psychology 19 12%
Neuroscience 17 11%
Other 9 6%
Unknown 31 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 04 July 2015.
All research outputs
#1,658,706
of 24,593,555 outputs
Outputs from Translational Psychiatry
#651
of 3,510 outputs
Outputs of similar age
#16,510
of 232,850 outputs
Outputs of similar age from Translational Psychiatry
#7
of 25 outputs
Altmetric has tracked 24,593,555 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,510 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has done well, scoring higher than 81% 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 232,850 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 25 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.