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Genetic variations and associated pathophysiology in the management of epilepsy

Overview of attention for article published in The Application of Clinical Genetics, August 2011
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Title
Genetic variations and associated pathophysiology in the management of epilepsy
Published in
The Application of Clinical Genetics, August 2011
DOI 10.2147/tacg.s7407
Pubmed ID
Authors

John C Mulley, Leanne M Dibbens

Abstract

The genomic era has enabled the application of molecular tools to the solution of many of the genetic epilepsies, with and without comorbidities. Massively parallel sequencing has recently reinvigorated gene discovery for the monogenic epilepsies. Recurrent and novel copy number variants have given much-needed impetus to the advancement of our understanding of epilepsies with complex inheritance. Superimposed upon that is the phenotypic blurring by presumed genetic modifiers scattering the effects of the primary mutation. The genotype-first approach has uncovered associated syndrome constellations, of which epilepsy is only one of the syndromes. As the molecular genetic basis for the epilepsies unravels, it will increasingly influence the classification and diagnosis of the epilepsies. The ultimate goal of the molecular revolution has to be the design of treatment protocols based on genetic profiles, and cracking the 30% of epilepsies refractory to current medications, but that still lies well into the future. The current focus is on the scientific basis for epilepsy. Understanding its genetic causes and biophysical mechanisms is where we are currently positioned: prizing the causes of epilepsy "out of the shadows" and exposing its underlying mechanisms beyond even the ion-channels.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 29%
Researcher 5 21%
Other 2 8%
Professor 2 8%
Lecturer > Senior Lecturer 1 4%
Other 2 8%
Unknown 5 21%
Readers by discipline Count As %
Medicine and Dentistry 8 33%
Agricultural and Biological Sciences 5 21%
Biochemistry, Genetics and Molecular Biology 3 13%
Computer Science 1 4%
Unknown 7 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 June 2013.
All research outputs
#20,247,404
of 25,748,735 outputs
Outputs from The Application of Clinical Genetics
#1
of 1 outputs
Outputs of similar age
#107,386
of 131,125 outputs
Outputs of similar age from The Application of Clinical Genetics
#1
of 1 outputs
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