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The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease

Overview of attention for article published in Scientific Data, September 2018
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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 (85th percentile)

Citations

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113 Mendeley
Title
The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
Published in
Scientific Data, September 2018
DOI 10.1038/sdata.2018.185
Pubmed ID
Authors

Minghui Wang, Noam D. Beckmann, Panos Roussos, Erming Wang, Xianxiao Zhou, Qian Wang, Chen Ming, Ryan Neff, Weiping Ma, John F. Fullard, Mads E. Hauberg, Jaroslav Bendl, Mette A. Peters, Ben Logsdon, Pei Wang, Milind Mahajan, Lara M. Mangravite, Eric B. Dammer, Duc M. Duong, James J. Lah, Nicholas T. Seyfried, Allan I. Levey, Joseph D. Buxbaum, Michelle Ehrlich, Sam Gandy, Pavel Katsel, Vahram Haroutunian, Eric Schadt, Bin Zhang

Abstract

Alzheimer's disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LOAD), but these risk loci fail to account for the majority of affected cases and can neither provide clinically meaningful prediction of development of AD nor offer actionable mechanisms. This cohort study generated large-scale matched multi-Omics data in AD and control brains for exploring novel molecular underpinnings of AD. Specifically, we generated whole genome sequencing, whole exome sequencing, transcriptome sequencing and proteome profiling data from multiple regions of 364 postmortem control, mild cognitive impaired (MCI) and AD brains with rich clinical and pathophysiological data. All the data went through rigorous quality control. Both the raw and processed data are publicly available through the Synapse software platform.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 113 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 27%
Student > Ph. D. Student 23 20%
Student > Bachelor 12 11%
Other 11 10%
Professor > Associate Professor 9 8%
Other 14 12%
Unknown 13 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 31 27%
Agricultural and Biological Sciences 21 19%
Neuroscience 10 9%
Medicine and Dentistry 5 4%
Engineering 4 4%
Other 20 18%
Unknown 22 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 19 December 2018.
All research outputs
#1,182,087
of 14,056,657 outputs
Outputs from Scientific Data
#350
of 1,047 outputs
Outputs of similar age
#38,116
of 270,406 outputs
Outputs of similar age from Scientific Data
#1
of 1 outputs
Altmetric has tracked 14,056,657 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,047 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.0. This one has gotten more attention than average, scoring higher than 66% 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 270,406 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 85% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them