Distinguishing Loss-of-Function and Gain-of-Function <i>SCN8A</i> Variants Using a Random Forest Classification Model Trained on Clinical Features-Reference-Cited by-同舟云学术

Distinguishing Loss-of-Function and Gain-of-Function SCN8A Variants Using a Random Forest Classification Model Trained on Clinical Features

Published:2023-06 Issue:3 Volume:9 Page:
ISSN:2376-7839
Container-title:Neurology Genetics
language:en
Short-container-title:Neurol Genet

Author:

Hack Joshua B.¹,Horning Kyle¹,Juroske Short Denise M.¹,Schreiber John M.¹,Watkins Joseph C.¹,Hammer Michael F.¹

Affiliation:

1. From the BIO5 Institute (J.B.H., M.F.H.), University of Arizona, Tucson; CombinedBrain (K.H.), Brentwood; DenGen Consulting (D.M.J.S.), Rocky Top, TN; Children's National Medical Center (J.M.S.), Department of Neurology, Washington, DC; Department of Mathematics (J.C.W.), University of Arizona; and Neurology Department (M.F.H.), University of Arizona, Tucson.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Genetics (clinical),Neurology (clinical)

Link

https://www.neurology.org/doi/pdfdirect/10.1212/NXG.0000000000200060

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3. Functional correlates of clinical phenotype and severity in recurrent SCN2A variants;Berecki G;Commun Biol.,2022

4. Sodium channelopathies in neurodevelopmental disorders

5. Genotype-phenotype correlations in SCN8A-related disorders reveal prognostic and therapeutic implications

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