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Rett syndrome – biological pathways leading from MECP2 to disorder phenotypes

Overview of attention for article published in Orphanet Journal of Rare Diseases, November 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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6 X users
wikipedia
3 Wikipedia pages

Citations

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68 Dimensions

Readers on

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247 Mendeley
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2 CiteULike
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Title
Rett syndrome – biological pathways leading from MECP2 to disorder phenotypes
Published in
Orphanet Journal of Rare Diseases, November 2016
DOI 10.1186/s13023-016-0545-5
Pubmed ID
Authors

Friederike Ehrhart, Susan L. M. Coort, Elisa Cirillo, Eric Smeets, Chris T. Evelo, Leopold M. G. Curfs

Abstract

Rett syndrome (RTT) is a rare disease but still one of the most abundant causes for intellectual disability in females. Typical symptoms are onset at month 6-18 after normal pre- and postnatal development, loss of acquired skills and severe intellectual disability. The type and severity of symptoms are individually highly different. A single mutation in one gene, coding for methyl-CpG-binding protein 2 (MECP2), is responsible for the disease. The most important action of MECP2 is regulating epigenetic imprinting and chromatin condensation, but MECP2 influences many different biological pathways on multiple levels although the molecular pathways from gene to phenotype are currently not fully understood. In this review the known changes in metabolite levels, gene expression and biological pathways in RTT are summarized, discussed how they are leading to some characteristic RTT phenotypes and therefore the gaps of knowledge are identified. Namely, which phenotypes have currently no mechanistic explanation leading back to MECP2 related pathways? As a result of this review the visualization of the biologic pathways showing MECP2 up- and downstream regulation was developed and published on WikiPathways which will serve as template for future omics data driven research. This pathway driven approach may serve as a use case for other rare diseases, too.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 247 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Netherlands 1 <1%
Unknown 245 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 16%
Student > Bachelor 39 16%
Student > Master 33 13%
Researcher 28 11%
Student > Postgraduate 10 4%
Other 31 13%
Unknown 67 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 20%
Medicine and Dentistry 31 13%
Neuroscience 28 11%
Agricultural and Biological Sciences 23 9%
Nursing and Health Professions 7 3%
Other 36 15%
Unknown 72 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 06 August 2022.
All research outputs
#4,869,680
of 24,143,470 outputs
Outputs from Orphanet Journal of Rare Diseases
#672
of 2,829 outputs
Outputs of similar age
#92,212
of 423,456 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#15
of 35 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,829 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 76% 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 423,456 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 78% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.